# ANALISIS MGWR FIXED BANDWIDTH - TB RATE 514 KABUPATEN/KOTA
# ---------------------- BAGIAN KODE 1 ----------------------
EXCEL_FILE <- "D:/STATISTIKA/SEM 5/Analisis Data Spasial/Materi Pekan 1-8/Tugas Project GWR/Data Spasial_TBC/Data TBC Kabupaten Kota di Indonesia/Data TBC.xlsx"
SHP_FILE <- "D:/STATISTIKA/SEM 5/Analisis Data Spasial/Materi Pekan 1-8/Tugas Project GWR/BATAS/Batas_Kabupaten_Kota.gpkg"
SHP_NAME_FIELD <- "WADMKK"
Y_TRANSFORM <- "raw"
STANDARDIZE <- TRUE
RUN_KERNEL_COMPARISON <- FALSE
KERNEL_CANDIDATES <- c("exponential")
KERNEL_DEFAULT <- "exponential"
ADAPTIVE <- FALSE
LONG_LAT <- TRUE
K_MORAN <- 8
MGWR_CRITERION <- "dCVR"
MGWR_APPROACH <- "AIC"
MGWR_MAX_ITER <- 2000
MGWR_THRESHOLD <- 1e-5
MGWR_REOPT <- 5
MGWR_NLOWER <- 10
RUN_MONTE_CARLO <- TRUE
MC_SIM <- 99
T_CRIT <- 1.96
set.seed(123)
# ---------------------- BAGIAN KODE 2 ----------------------
pkgs <- c("readxl", "dplyr", "sf", "sp", "spdep", "car", "lmtest",
"GWmodel", "ggplot2", "corrplot", "DT", "knitr", "rmarkdown")
new_pkgs <- pkgs[!sapply(pkgs, requireNamespace, quietly = TRUE)]
if(length(new_pkgs) > 0) install.packages(new_pkgs, dependencies = TRUE)
library(readxl); library(dplyr); library(sf); library(sp); library(spdep)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
## Linking to GEOS 3.14.1, GDAL 3.12.1, PROJ 9.7.1; sf_use_s2() is TRUE
## Loading required package: spData
## To access larger datasets in this package, install the spDataLarge
## package with: `install.packages('spDataLarge',
## repos='https://nowosad.github.io/drat/', type='source')`
library(car); library(lmtest); library(GWmodel); library(ggplot2); library(corrplot)
## Loading required package: carData
##
## Attaching package: 'car'
## The following object is masked from 'package:dplyr':
##
## recode
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
## Loading required package: robustbase
## Loading required package: Rcpp
## Welcome to GWmodel version 2.4-2.
## corrplot 0.95 loaded
sf_use_s2(FALSE)
## Spherical geometry (s2) switched off
OUT <- "hasil_MGWR_TBC_fixed"
MAP <- file.path(OUT, "peta")
dir.create(OUT, showWarnings = FALSE, recursive = TRUE)
dir.create(MAP, showWarnings = FALSE, recursive = TRUE)
# ---------------------- BAGIAN KODE 3 ----------------------
clean_text <- function(x){
x <- toupper(trimws(as.character(x)))
x <- gsub("[’']", "", x)
x <- gsub("\\.", " ", x)
x <- gsub("&", " DAN ", x, fixed = TRUE)
x <- gsub("[^A-Z0-9 ]", " ", x)
x <- gsub("\\s+", " ", x)
trimws(x)
}
remove_prefix <- function(x){
x <- clean_text(x)
x <- gsub("^KABUPATEN\\s+", "", x)
x <- gsub("^KAB\\s+", "", x)
x <- gsub("^KOTA ADMINISTRATIF\\s+", "", x)
x <- gsub("^KOTA\\s+", "", x)
x <- gsub("^REGENCY\\s+", "", x)
x <- gsub("^CITY\\s+", "", x)
trimws(x)
}
get_type <- function(x){
z <- clean_text(x)
ifelse(grepl("KABUPATEN|KAB |REGENCY", z), "KABUPATEN",
ifelse(grepl("KOTA|CITY", z), "KOTA", NA_character_))
}
make_key <- function(type, name) paste0(type, "|", remove_prefix(name))
save_txt <- function(x, file){
capture.output(print(x), file = file.path(OUT, file))
}
get_stat <- function(obj, candidates){
if(is.null(obj)) return(NA_real_)
for(nm in candidates){
if(nm %in% names(obj)){
v <- suppressWarnings(as.numeric(obj[[nm]][1]))
if(length(v) == 1 && is.finite(v)) return(v)
}
}
NA_real_
}
find_col <- function(df, candidates){
nm <- names(df)
for(cand in candidates){
hit <- nm[tolower(nm) == tolower(cand)]
if(length(hit) > 0) return(hit[1])
}
NA_character_
}
# AICc OLS: AIC + koreksi sampel kecil.
# k menghitung parameter regresi dan parameter varians residual.
aicc_ols <- function(m){
nn <- stats::nobs(m)
kk <- length(stats::coef(m)) + 1L
if(nn <= kk + 1L) return(NA_real_)
stats::AIC(m) + (2 * kk * (kk + 1)) / (nn - kk - 1)
}
save_map <- function(sf_obj, col, title, file, diverging = FALSE, legend = "Nilai"){
p <- ggplot(sf_obj) +
geom_sf(aes(fill = .data[[col]]), color = "grey70", linewidth = 0.03) +
theme_void() + labs(title = title, fill = legend)
p <- if(diverging){
p + scale_fill_gradient2(low = "blue", mid = "white", high = "red",
midpoint = 0, na.value = "grey85")
}else{
p + scale_fill_viridis_c(option = "C", na.value = "grey85")
}
ggsave(file.path(MAP, file), p, width = 12, height = 6, dpi = 300)
}
# ---------------------- BAGIAN KODE 4 ----------------------
if(!file.exists(EXCEL_FILE)) stop("File Excel tidak ditemukan di working directory.")
raw <- read_excel(EXCEL_FILE, sheet = 1)
cat("Jumlah baris Excel:", nrow(raw), "\n"); print(names(raw))
## Jumlah baris Excel: 514
## [1] "Kabupaten/Kota"
## [2] "TB_Rate_per100.000_Penduduk"
## [3] "Persentase_Penduduk_Miskin"
## [4] "Persentase_Rumah_Tangga_dengan_Sanitasi_Layak"
## [5] "Persentase_Penduduk15_yangMerokok"
## [6] "Persentase_Rumah_Tangga_Memiliki_Akses_Hunian_Layak"
required_cols <- c(
"Kabupaten/Kota",
"TB_Rate_per100.000_Penduduk",
"Persentase_Penduduk_Miskin",
"Persentase_Rumah_Tangga_dengan_Sanitasi_Layak",
"Persentase_Penduduk15_yangMerokok",
"Persentase_Rumah_Tangga_Memiliki_Akses_Hunian_Layak"
)
if(!all(required_cols %in% names(raw))){
stop("Nama kolom Excel berbeda. Kolom yang hilang: ",
paste(setdiff(required_cols, names(raw)), collapse = ", "))
}
data <- raw %>%
transmute(
id = row_number(),
wilayah = as.character(`Kabupaten/Kota`),
Y_TB = as.numeric(`TB_Rate_per100.000_Penduduk`),
X1_miskin = as.numeric(`Persentase_Penduduk_Miskin`),
X2_sanitasi = as.numeric(`Persentase_Rumah_Tangga_dengan_Sanitasi_Layak`),
X3_merokok = as.numeric(`Persentase_Penduduk15_yangMerokok`),
X4_hunian = as.numeric(`Persentase_Rumah_Tangga_Memiliki_Akses_Hunian_Layak`)
) %>%
as.data.frame()
data$jenis <- get_type(data$wilayah)
data$nama_dasar <- remove_prefix(data$wilayah)
data$key <- make_key(data$jenis, data$nama_dasar)
xvars <- c("X1_miskin", "X2_sanitasi", "X3_merokok", "X4_hunian")
vars <- c("Y_TB", xvars)
# Audit data
miss <- data.frame(variable = vars, n_missing = sapply(data[vars], function(x) sum(is.na(x))))
write.csv(miss, file.path(OUT, "01_missing.csv"), row.names = FALSE)
if(any(miss$n_missing > 0)) stop("Ada missing value. Lihat 01_missing.csv")
if(Y_TRANSFORM == "log" && any(data$Y_TB <= 0)) stop("TB rate harus > 0 untuk transformasi log.")
if(anyDuplicated(data$key) > 0) stop("Ada wilayah duplikat di Excel setelah normalisasi nama.")
if(nrow(data) != 514) warning("Jumlah baris bukan 514: ", nrow(data))
if(any(sapply(data[xvars], sd) == 0)) stop("Ada prediktor dengan variasi nol.")
write.csv(data, file.path(OUT, "02_data_clean.csv"), row.names = FALSE)
# ---------------------- BAGIAN KODE 5 ----------------------
# Memastikan file GeoPackage tersedia
if (!file.exists(SHP_FILE)) {
stop("File GeoPackage tidak ditemukan: ", SHP_FILE)
}
# Baca layer kabupaten/kota
print(sf::st_layers(SHP_FILE))
## Driver: GPKG
## Available layers:
## layer_name geometry_type features fields crs_name
## 1 kabupaten_kota 514 3 WGS 84
admin <- sf::st_read(
SHP_FILE,
layer = "kabupaten_kota",
quiet = TRUE
)
# Periksa kolom nama wilayah
print(names(admin))
## [1] "KDPKAB" "WADMKK" "WADMPR" "geom"
# Gunakan kolom WADMKK sebagai nama wilayah
if (!SHP_NAME_FIELD %in% names(admin)) {
stop("Kolom ", SHP_NAME_FIELD, " tidak ditemukan dalam GeoPackage.")
}
admin$name_shape <- as.character(admin[[SHP_NAME_FIELD]])
# Tentukan jenis wilayah dari nama pada peta
admin$type_shape <- ifelse(
grepl("^KOTA\\s+", clean_text(admin$name_shape)),
"KOTA",
"KABUPATEN"
)
admin$name_only <- remove_prefix(admin$name_shape)
# Alias nama untuk menyamakan ejaan Excel dan peta
alias_nama <- c(
"TOBA SAMOSIR" = "TOBA",
"LABUHAN BATU" = "LABUHANBATU",
"LABUHAN BATU SELATAN" = "LABUHANBATU SELATAN",
"LABUHAN BATU UTARA" = "LABUHANBATU UTARA",
"TANJUNG BALAI" = "TANJUNGBALAI",
"PEMATANG SIANTAR" = "PEMATANGSIANTAR",
"SAWAH LUNTO" = "SAWAHLUNTO",
"BATANG HARI" = "BATANGHARI",
"BANYU ASIN" = "BANYUASIN",
"PENUKAL ABAB" = "PENUKAL ABAB LEMATANG ILIR",
"LUBUKLINGGAU" = "LUBUK LINGGAU",
"TULANGBAWANG" = "TULANG BAWANG",
"KEPULAUAN SERIBU" = "ADMINISTRASI KEPULAUAN SERIBU",
"JAKARTA SELATAN" = "ADMINISTRASI JAKARTA SELATAN",
"JAKARTA TIMUR" = "ADMINISTRASI JAKARTA TIMUR",
"JAKARTA PUSAT" = "ADMINISTRASI JAKARTA PUSAT",
"JAKARTA BARAT" = "ADMINISTRASI JAKARTA BARAT",
"JAKARTA UTARA" = "ADMINISTRASI JAKARTA UTARA",
"GUNUNG KIDUL" = "GUNUNGKIDUL",
"PALANGKA RAYA" = "PALANGKARAYA",
"BANJAR BARU" = "BANJARBARU",
"MAHAKAM HULU" = "MAHAKAM ULU",
"BAUBAU" = "BAU BAU",
"MALUKU TENGGARA BARAT" = "KEPULAUAN TANIMBAR",
"FAKFAK" = "FAK FAK"
)
# Normalisasi nama dari Excel
data$name_match <- data$nama_dasar
hit_alias <- data$name_match %in% names(alias_nama)
data$name_match[hit_alias] <-
unname(alias_nama[data$name_match[hit_alias]])
# Normalisasi nama pada peta
admin$name_match <- admin$name_only
# Buat kunci gabungan jenis dan nama
data$key_match <- paste(data$jenis, data$name_match, sep = "|")
admin$key_match <- paste(admin$type_shape, admin$name_match, sep = "|")
# Periksa jumlah wilayah
cat("Jumlah baris Excel:", nrow(data), "\n")
## Jumlah baris Excel: 514
cat("Jumlah fitur GeoPackage:", nrow(admin), "\n")
## Jumlah fitur GeoPackage: 514
if (nrow(admin) != 514) {
stop("Jumlah fitur GeoPackage bukan 514. Periksa layer yang dibaca.")
}
# Audit geometri: simpan laporan dan hentikan proses bila geometri kosong/tidak valid.
geom_audit <- data.frame(
n_fitur = nrow(admin),
n_geometri_kosong = sum(sf::st_is_empty(admin)),
n_geometri_tidak_valid = sum(!sf::st_is_valid(admin), na.rm = TRUE)
)
write.csv(geom_audit, file.path(OUT, "03_geometry_audit.csv"), row.names = FALSE)
if (geom_audit$n_geometri_kosong > 0 || geom_audit$n_geometri_tidak_valid > 0) {
stop("Ada geometri kosong/tidak valid. Periksa 03_geometry_audit.csv sebelum analisis.")
}
# Periksa apakah kunci peta duplikat
if (anyDuplicated(admin$key_match) > 0) {
print(admin[duplicated(admin$key_match),
c("WADMKK", "WADMPR", "KDPKAB", "key_match")])
stop("Kunci jenis dan nama wilayah pada peta duplikat.")
}
# Cocokkan urutan wilayah Excel dengan peta
idx <- match(data$key_match, admin$key_match)
cat("Wilayah tidak cocok:", sum(is.na(idx)), "\n")
## Wilayah tidak cocok: 0
if (any(is.na(idx))) {
print(data[is.na(idx),
c("id", "wilayah", "jenis", "name_match")])
stop("Matching belum lengkap. Periksa nama wilayah yang tidak cocok.")
}
if (anyDuplicated(idx) > 0) {
stop("Ada geometri yang digunakan lebih dari sekali.")
}
# Gabungkan data dan geometri
analysis_poly <- sf::st_sf(
data,
geometry = sf::st_geometry(admin)[idx]
)
stopifnot(
nrow(analysis_poly) == 514,
all(analysis_poly$id == data$id)
)
cat("\nMATCHING BERHASIL\n")
##
## MATCHING BERHASIL
cat("Jumlah observasi:", nrow(analysis_poly), "\n")
## Jumlah observasi: 514
cat("Jumlah geometri:", nrow(analysis_poly), "\n")
## Jumlah geometri: 514
cat("Wilayah tidak cocok:", sum(is.na(idx)), "\n")
## Wilayah tidak cocok: 0
# ---------------------- BAGIAN KODE 6 ----------------------
desc <- do.call(rbind, lapply(vars, function(v){
x <- data[[v]]
data.frame(variable = v, n = length(x), mean = mean(x), sd = sd(x), min = min(x),
Q1 = unname(quantile(x, .25)), median = median(x),
Q3 = unname(quantile(x, .75)), max = max(x))
}))
write.csv(desc, file.path(OUT, "04_descriptive_statistics.csv"), row.names = FALSE)
print(desc, digits = 4)
## variable n mean sd min Q1 median Q3 max
## 1 Y_TB 514 283.62 185.442 10.28 168.194 228.577 349.68 1478.43
## 2 X1_miskin 514 10.58 6.954 1.90 5.962 8.745 12.78 42.56
## 3 X2_sanitasi 514 82.77 17.156 0.00 77.763 88.190 93.46 100.00
## 4 X3_merokok 514 28.47 5.523 3.64 25.203 28.835 32.37 45.69
## 5 X4_hunian 514 66.38 19.685 0.00 57.898 70.305 80.58 98.41
# ---------------------- BAGIAN KODE 7 ----------------------
cor_all <- cor(data[vars])
write.csv(cor_all, file.path(OUT, "05_correlation_matrix.csv"))
cor_YX <- do.call(rbind, lapply(xvars, function(v){
ct <- cor.test(data$Y_TB, data[[v]])
data.frame(variable = v, r = unname(ct$estimate), p_value = ct$p.value)
}))
write.csv(cor_YX, file.path(OUT, "06_correlation_Y_X.csv"), row.names = FALSE)
print(cor_YX)
## variable r p_value
## 1 X1_miskin -0.078394678 0.07577631
## 2 X2_sanitasi 0.029445203 0.50535480
## 3 X3_merokok -0.101380525 0.02151715
## 4 X4_hunian 0.003412044 0.93848968
vif_awal <- car::vif(lm(Y_TB ~ X1_miskin + X2_sanitasi + X3_merokok + X4_hunian, data = data))
write.csv(data.frame(variable = names(vif_awal), VIF = as.numeric(vif_awal)),
file.path(OUT, "07_VIF_awal.csv"), row.names = FALSE)
print(vif_awal)
## X1_miskin X2_sanitasi X3_merokok X4_hunian
## 1.546557 3.196714 1.019062 2.738406
# ---------------------- BAGIAN KODE 8 ----------------------
data$Y_model <- if(Y_TRANSFORM == "log") log(data$Y_TB) else data$Y_TB
model_vars <- c("Y_model", xvars)
mdat <- data[, c("id", "wilayah", model_vars)]
if(STANDARDIZE) mdat[model_vars] <- lapply(mdat[model_vars], function(x) as.numeric(scale(x)))
formula_model <- Y_model ~ X1_miskin + X2_sanitasi + X3_merokok + X4_hunian
# ---------------------- BAGIAN KODE 9 ----------------------
OLS <- lm(formula_model, data = mdat)
save_txt(summary(OLS), "08_OLS_summary.txt")
write.csv(as.data.frame(coef(summary(OLS))), file.path(OUT, "09_OLS_coefficients.csv"))
n <- nrow(mdat)
save_txt(resettest(OLS, power = 2:3, type = "fitted"), "10_RESET.txt")
save_txt(shapiro.test(residuals(OLS)), "11_Shapiro_Wilk.txt")
# Uji Breusch-Pagan manual berdasarkan rumus matriks
bp_e <- as.numeric(residuals(OLS))
bp_n <- length(bp_e)
bp_sigma2 <- sum(bp_e^2) / bp_n
bp_Z <- model.matrix(OLS)[, -1, drop = FALSE]
bp_f <- (bp_e^2 / bp_sigma2) - 1
bp_ztz <- crossprod(bp_Z)
if (qr(bp_ztz)$rank < ncol(bp_ztz)) {
stop("Matriks Z'Z singular pada uji BP manual.")
}
bp_stat <- as.numeric(0.5 * t(bp_f) %*% bp_Z %*%
solve(bp_ztz) %*% t(bp_Z) %*% bp_f)
bp_df <- ncol(bp_Z)
bp_p <- pchisq(bp_stat, df = bp_df, lower.tail = FALSE)
BP_MANUAL <- data.frame(
statistic = bp_stat, df = bp_df,
chi_square_critical = qchisq(0.95, df = bp_df),
p_value = bp_p,
decision = ifelse(bp_p < 0.05, "Tolak H0", "Gagal menolak H0"),
method = "Breusch-Pagan manual berbasis rumus matriks"
)
write.csv(BP_MANUAL, file.path(OUT, "12_Breusch_Pagan_manual.csv"), row.names = FALSE)
save_txt(BP_MANUAL, "12_Breusch_Pagan_manual.txt")
vif_ols <- car::vif(OLS)
write.csv(data.frame(variable = names(vif_ols), VIF = as.numeric(vif_ols)),
file.path(OUT, "13_VIF_OLS.csv"), row.names = FALSE)
cook <- cooks.distance(OLS)
write.csv(data.frame(id = mdat$id, wilayah = mdat$wilayah, Cook_D = cook) %>% arrange(desc(Cook_D)),
file.path(OUT, "14_Cooks_distance.csv"), row.names = FALSE)
AICc_OLS <- aicc_ols(OLS)
# ---------------------- BAGIAN KODE 10 ----------------------
poly_proj <- st_transform(analysis_poly, 3857)
pts_geom <- st_transform(
st_point_on_surface(st_geometry(poly_proj)), 4326
)
xy <- st_coordinates(pts_geom)
colnames(xy) <- c("lon", "lat")
write.csv(
data.frame(id = mdat$id, wilayah = mdat$wilayah, xy),
file.path(OUT, "15_coordinates.csv"),
row.names = FALSE
)
pts_sp <- SpatialPointsDataFrame(
coords = xy,
data = as.data.frame(mdat),
proj4string = CRS("+proj=longlat +datum=WGS84 +no_defs")
)
# Matriks bobot spasial KNN 8
knn_nb <- knn2nb(
knearneigh(xy, k = K_MORAN, longlat = TRUE)
)
listw_knn <- nb2listw(
knn_nb,
style = "W",
zero.policy = TRUE
)
# Ringkasan matriks bobot KNN 8
write.csv(
data.frame(
weights = "KNN-8",
n = length(knn_nb),
min_nb = min(card(knn_nb)),
median_nb = median(card(knn_nb)),
max_nb = max(card(knn_nb))
),
file.path(OUT, "16_weights_summary.csv"),
row.names = FALSE
)
# Analisis sensitivitas Moran's I untuk beberapa nilai KNN.
knn_sensitivity <- do.call(rbind, lapply(c(4, 8, 12), function(k) {
nb_k <- knn2nb(knearneigh(xy, k = k, longlat = TRUE))
lw_k <- nb2listw(nb_k, style = "W", zero.policy = TRUE)
mt_k <- moran.test(mdat$Y_model, lw_k, randomisation = TRUE,
alternative = "two.sided", zero.policy = TRUE)
data.frame(K = k, Moran_I = unname(mt_k$estimate[["Moran I statistic"]]),
expectation = unname(mt_k$estimate[["Expectation"]]),
variance = unname(mt_k$estimate[["Variance"]]),
p_value = mt_k$p.value)
}))
## Warning in knn2nb(knearneigh(xy, k = k, longlat = TRUE)): neighbour object has
## 4 sub-graphs
write.csv(knn_sensitivity, file.path(OUT, "16a_Moran_sensitivity_KNN.csv"), row.names = FALSE)
# ---------------------- BAGIAN KODE 11 ----------------------
save_txt(
moran.test(
mdat$Y_model,
listw_knn,
randomisation = TRUE,
alternative = "two.sided",
zero.policy = TRUE
),
"17_Moran_Y_KNN8.txt"
)
save_txt(
lm.morantest(
OLS,
listw_knn,
zero.policy = TRUE
),
"19_Moran_OLS_residual_KNN8.txt"
)
# ---------------------- BAGIAN KODE 12 ----------------------
cat("\n===== GWR: PEMILIHAN KERNEL DAN BANDWIDTH =====\n")
##
## ===== GWR: PEMILIHAN KERNEL DAN BANDWIDTH =====
kernels_to_run <- if(RUN_KERNEL_COMPARISON) KERNEL_CANDIDATES else KERNEL_DEFAULT
kernel_table <- do.call(rbind, lapply(kernels_to_run, function(k){
cat("Kernel:", k, "\n")
bw <- bw.gwr(formula_model, data = pts_sp, approach = "AICc", kernel = k,
adaptive = ADAPTIVE, longlat = LONG_LAT)
m <- gwr.basic(formula_model, data = pts_sp, bw = bw, kernel = k,
adaptive = ADAPTIVE, longlat = LONG_LAT)
data.frame(kernel = k, bandwidth = bw,
AICc = get_stat(m$GW.diagnostic, "AICc"),
R2 = get_stat(m$GW.diagnostic, c("gw.R2", "R2.val")),
stringsAsFactors = FALSE)
}))
## Kernel: exponential
## Fixed bandwidth: 3205.717 AICc value: 1427.306
## Fixed bandwidth: 1981.638 AICc value: 1410.505
## Fixed bandwidth: 1225.116 AICc value: 1386.293
## Fixed bandwidth: 757.5595 AICc value: 1350.498
## Fixed bandwidth: 468.5937 AICc value: 1302.395
## Fixed bandwidth: 290.003 AICc value: 1264.54
## Fixed bandwidth: 179.6279 AICc value: 1269.55
## Fixed bandwidth: 358.2186 AICc value: 1277.605
## Fixed bandwidth: 247.8435 AICc value: 1260.102
## Fixed bandwidth: 221.7875 AICc value: 1260.229
## Fixed bandwidth: 263.947 AICc value: 1261.272
## Fixed bandwidth: 237.891 AICc value: 1259.81
## Fixed bandwidth: 231.74 AICc value: 1259.827
## Fixed bandwidth: 241.6925 AICc value: 1259.877
## Fixed bandwidth: 235.5415 AICc value: 1259.797
## Fixed bandwidth: 234.0895 AICc value: 1259.801
## Fixed bandwidth: 236.4389 AICc value: 1259.799
## Fixed bandwidth: 234.9869 AICc value: 1259.797
## Fixed bandwidth: 235.8843 AICc value: 1259.797
## Fixed bandwidth: 235.3297 AICc value: 1259.797
write.csv(kernel_table, file.path(OUT, "21_GWR_kernel_comparison.csv"), row.names = FALSE)
print(kernel_table)
## kernel bandwidth AICc R2
## 1 exponential 235.5415 1259.797 0.518633
best <- if(all(is.na(kernel_table$AICc))) 1 else which.min(kernel_table$AICc)
KERNEL <- kernel_table$kernel[best]
BW_GWR <- kernel_table$bandwidth[best]
cat("Kernel terpilih:", KERNEL, "| Bandwidth GWR:", BW_GWR, "| Mode:", if (ADAPTIVE) "adaptive" else "fixed", "\n")
## Kernel terpilih: exponential | Bandwidth GWR: 235.5415 | Mode: fixed
GWR <- gwr.basic(formula_model, data = pts_sp, bw = BW_GWR, kernel = KERNEL,
adaptive = ADAPTIVE, longlat = LONG_LAT, F123.test = TRUE, cv = FALSE)
## Warning in pf(F2, F2.DF[1], F2.DF[2], lower.tail = FALSE): NaNs produced
save_txt(GWR, "22_GWR_summary.txt")
# Simpan hasil uji F Leung (F1, F2, F3) jika tersedia dari GWmodel
save_txt(GWR$Ftest.res, "22a_GWR_Leung_F_tests.txt")
GWR_DF <- as.data.frame(GWR$SDF)
GWR_DF$id <- mdat$id; GWR_DF$wilayah <- mdat$wilayah
write.csv(GWR_DF, file.path(OUT, "23_GWR_local_results.csv"), row.names = FALSE)
# Diagnostik GWR: multikolinearitas lokal
GWR_COLLIN <- gwr.collin.diagno(formula_model, data = pts_sp, bw = BW_GWR, kernel = KERNEL,
adaptive = ADAPTIVE, longlat = LONG_LAT)
if(!is.null(GWR_COLLIN$SDF)){
coll_df <- as.data.frame(GWR_COLLIN$SDF)
write.csv(coll_df, file.path(OUT, "24_GWR_local_collinearity.csv"), row.names = FALSE)
save_txt(summary(coll_df), "25_GWR_local_collinearity_summary.txt")
# Ringkasan condition number lokal, jika kolom tersedia
cn_col <- find_col(coll_df, c("local_CN", "Local_CN"))
if(!is.na(cn_col)){
cn <- as.numeric(coll_df[[cn_col]])
cn_valid <- is.finite(cn)
if(any(cn_valid)){
cn_summary <- data.frame(
n_lokasi = sum(cn_valid),
CN_min = min(cn[cn_valid]),
CN_median = median(cn[cn_valid]),
CN_max = max(cn[cn_valid]),
n_CN_gt30 = sum(cn[cn_valid] > 30),
persen_CN_gt30 = 100 * mean(cn[cn_valid] > 30)
)
write.csv(cn_summary, file.path(OUT, "25a_GWR_local_CN_summary.csv"), row.names = FALSE)
}
}
}
# Uji Monte Carlo (opsional) dengan validasi bandwidth dan penanganan error.
if (RUN_MONTE_CARLO) {
dp_n <- nrow(pts_sp@data)
bw_ok <- is.finite(BW_GWR) && length(BW_GWR) == 1 &&
if (ADAPTIVE) BW_GWR < dp_n else BW_GWR > 0
if (!bw_ok) {
mc_note <- paste0(
"Monte Carlo tidak dijalankan: bandwidth tidak memenuhi syarat. BW_GWR=",
BW_GWR, "; jumlah observasi=", dp_n,
". Periksa bandwidth dan dokumentasi GWmodel."
)
writeLines(mc_note, file.path(OUT, "26_GWR_MonteCarlo.txt"))
message(mc_note)
} else {
MC <- tryCatch(
gwr.montecarlo(formula_model, data = pts_sp, nsim = MC_SIM,
kernel = KERNEL, adaptive = ADAPTIVE,
bw = BW_GWR, longlat = LONG_LAT),
error = function(e) {
msg <- paste("Uji Monte Carlo gagal:", conditionMessage(e))
writeLines(msg, file.path(OUT, "26_GWR_MonteCarlo.txt"))
message(msg)
NULL
}
)
if (!is.null(MC)) save_txt(MC, "26_GWR_MonteCarlo.txt")
}
}
##
## Tests based on the Monte Carlo significance test
##
## p-value
## (Intercept) 0.00
## X1_miskin 0.00
## X2_sanitasi 0.04
## X3_merokok 0.18
## X4_hunian 0.03
# Moran residual GWR
res_col_g <- find_col(GWR_DF, "residual")
if(!is.na(res_col_g)){
save_txt(moran.test(GWR_DF[[res_col_g]], listw_knn, randomisation = TRUE,
alternative = "two.sided", zero.policy = TRUE), "27_Moran_GWR_residual.txt")
}
# ---------------------- BAGIAN KODE 13 ----------------------
cat("\n===== MGWR / BACKFITTING =====\n")
##
## ===== MGWR / BACKFITTING =====
p_par <- length(xvars) + 1
MGWR <- gwr.multiscale(
formula = formula_model,
data = pts_sp,
kernel = KERNEL,
adaptive = ADAPTIVE,
criterion = MGWR_CRITERION,
approach = MGWR_APPROACH,
bws0 = rep(BW_GWR, p_par),
bw.seled = rep(FALSE, p_par),
bws.reOpts = MGWR_REOPT,
max.iterations = MGWR_MAX_ITER,
threshold = MGWR_THRESHOLD,
predictor.centered = rep(TRUE, length(xvars)),
hatmatrix = TRUE,
longlat = LONG_LAT,
verbose = FALSE,
nlower = MGWR_NLOWER
)
## Calculate the initial beta0 from the above bandwidths.
## End of calculating the inital beta0.
## Find the optimum bandwidths for each independent variable.
## Iteration 1
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 153.572
## The bandwidth used in the last iteration is: 235.542 and the difference in bandwidths is: 81.9696
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 218.541
## The bandwidth used in the last iteration is: 235.542 and the difference in bandwidths is: 17.0009
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 263.947
## The bandwidth used in the last iteration is: 235.542 and the difference in bandwidths is: 28.4055
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 420.283
## The bandwidth used in the last iteration is: 235.542 and the difference in bandwidths is: 184.742
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 214.184
## The bandwidth used in the last iteration is: 235.542 and the difference in bandwidths is: 21.3571
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 1 change of RSS (dCVR) is 0.29489.
## Iteration 2
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 143.962
## The bandwidth used in the last iteration is: 153.572 and the difference in bandwidths is: 9.60973
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 229.391
## The bandwidth used in the last iteration is: 218.541 and the difference in bandwidths is: 10.8499
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 338.314
## The bandwidth used in the last iteration is: 263.947 and the difference in bandwidths is: 74.3666
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 747.607
## The bandwidth used in the last iteration is: 420.283 and the difference in bandwidths is: 327.324
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 241.138
## The bandwidth used in the last iteration is: 214.184 and the difference in bandwidths is: 26.9534
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 2 change of RSS (dCVR) is 0.123817.
## Iteration 3
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 137.257
## The bandwidth used in the last iteration is: 143.962 and the difference in bandwidths is: 6.70563
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 235.884
## The bandwidth used in the last iteration is: 229.391 and the difference in bandwidths is: 6.49378
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 440.188
## The bandwidth used in the last iteration is: 338.314 and the difference in bandwidths is: 101.875
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 893.991
## The bandwidth used in the last iteration is: 747.607 and the difference in bandwidths is: 146.384
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 261.598
## The bandwidth used in the last iteration is: 241.138 and the difference in bandwidths is: 20.4597
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 3 change of RSS (dCVR) is 0.0435257.
## Iteration 4
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 133.324
## The bandwidth used in the last iteration is: 137.257 and the difference in bandwidths is: 3.93245
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 242.035
## The bandwidth used in the last iteration is: 235.884 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 578.969
## The bandwidth used in the last iteration is: 440.188 and the difference in bandwidths is: 138.781
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 884.038
## The bandwidth used in the last iteration is: 893.991 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 279.153
## The bandwidth used in the last iteration is: 261.598 and the difference in bandwidths is: 17.5556
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 4 change of RSS (dCVR) is 0.0423748.
## Iteration 5
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 131.106
## The bandwidth used in the last iteration is: 133.324 and the difference in bandwidths is: 2.21854
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 247.843
## The bandwidth used in the last iteration is: 242.035 and the difference in bandwidths is: 5.80821
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 653.335
## The bandwidth used in the last iteration is: 578.969 and the difference in bandwidths is: 74.3666
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 861.784
## The bandwidth used in the last iteration is: 884.038 and the difference in bandwidths is: 22.2545
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 292.353
## The bandwidth used in the last iteration is: 279.153 and the difference in bandwidths is: 13.1994
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 5 change of RSS (dCVR) is 0.0152116.
## Iteration 6
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 129.865
## The bandwidth used in the last iteration is: 131.106 and the difference in bandwidths is: 1.2402
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 251.645
## The bandwidth used in the last iteration is: 247.843 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 679.391
## The bandwidth used in the last iteration is: 653.335 and the difference in bandwidths is: 26.056
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 854.181
## The bandwidth used in the last iteration is: 861.784 and the difference in bandwidths is: 7.60305
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 306.107
## The bandwidth used in the last iteration is: 292.353 and the difference in bandwidths is: 13.754
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 6 change of RSS (dCVR) is 0.031872.
## Iteration 7
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 128.625
## The bandwidth used in the last iteration is: 129.865 and the difference in bandwidths is: 1.2402
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 253.994
## The bandwidth used in the last iteration is: 251.645 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 693.145
## The bandwidth used in the last iteration is: 679.391 and the difference in bandwidths is: 13.754
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 845.68
## The bandwidth used in the last iteration is: 854.181 and the difference in bandwidths is: 8.50046
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 312.258
## The bandwidth used in the last iteration is: 306.107 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 7 change of RSS (dCVR) is 0.0399878.
## Iteration 8
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 127.859
## The bandwidth used in the last iteration is: 128.625 and the difference in bandwidths is: 0.766486
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 254.892
## The bandwidth used in the last iteration is: 253.994 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 699.296
## The bandwidth used in the last iteration is: 693.145 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 841.879
## The bandwidth used in the last iteration is: 845.68 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 319.861
## The bandwidth used in the last iteration is: 312.258 and the difference in bandwidths is: 7.60305
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 8 change of RSS (dCVR) is 0.0207501.
## Iteration 9
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 127.304
## The bandwidth used in the last iteration is: 127.859 and the difference in bandwidths is: 0.554635
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 254.892
## The bandwidth used in the last iteration is: 254.892 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 709.249
## The bandwidth used in the last iteration is: 699.296 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 831.926
## The bandwidth used in the last iteration is: 841.879 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 324.56
## The bandwidth used in the last iteration is: 319.861 and the difference in bandwidths is: 4.69894
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 9 change of RSS (dCVR) is 0.0300548.
## Iteration 10
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 126.961
## The bandwidth used in the last iteration is: 127.304 and the difference in bandwidths is: 0.342783
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 254.892
## The bandwidth used in the last iteration is: 254.892 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 715.4
## The bandwidth used in the last iteration is: 709.249 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 825.775
## The bandwidth used in the last iteration is: 831.926 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 332.163
## The bandwidth used in the last iteration is: 324.56 and the difference in bandwidths is: 7.60305
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 10 change of RSS (dCVR) is 0.0182516.
## Iteration 11
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 126.538
## The bandwidth used in the last iteration is: 126.961 and the difference in bandwidths is: 0.423703
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 255.447
## The bandwidth used in the last iteration is: 254.892 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 721.551
## The bandwidth used in the last iteration is: 715.4 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 815.823
## The bandwidth used in the last iteration is: 825.775 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 333.615
## The bandwidth used in the last iteration is: 332.163 and the difference in bandwidths is: 1.45205
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 11 change of RSS (dCVR) is 0.0319749.
## Iteration 12
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 126.407
## The bandwidth used in the last iteration is: 126.538 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 255.447
## The bandwidth used in the last iteration is: 255.447 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 727.702
## The bandwidth used in the last iteration is: 721.551 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 815.823
## The bandwidth used in the last iteration is: 815.823 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 334.512
## The bandwidth used in the last iteration is: 333.615 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 12 change of RSS (dCVR) is 0.0146413.
## Iteration 13
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 126.276
## The bandwidth used in the last iteration is: 126.407 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 255.447
## The bandwidth used in the last iteration is: 255.447 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 735.305
## The bandwidth used in the last iteration is: 727.702 and the difference in bandwidths is: 7.60305
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 809.672
## The bandwidth used in the last iteration is: 815.823 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 335.964
## The bandwidth used in the last iteration is: 334.512 and the difference in bandwidths is: 1.45205
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 13 change of RSS (dCVR) is 0.010571.
## Iteration 14
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 126.064
## The bandwidth used in the last iteration is: 126.276 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 254.892
## The bandwidth used in the last iteration is: 255.447 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 741.456
## The bandwidth used in the last iteration is: 735.305 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 805.87
## The bandwidth used in the last iteration is: 809.672 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 337.416
## The bandwidth used in the last iteration is: 335.964 and the difference in bandwidths is: 1.45205
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 14 change of RSS (dCVR) is 0.0219092.
## Iteration 15
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 125.933
## The bandwidth used in the last iteration is: 126.064 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 253.994
## The bandwidth used in the last iteration is: 254.892 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 747.607
## The bandwidth used in the last iteration is: 741.456 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 809.672
## The bandwidth used in the last iteration is: 805.87 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 338.314
## The bandwidth used in the last iteration is: 337.416 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X4_hunian will be continually selected in the next iteration.
## Iteration 15 change of RSS (dCVR) is 0.0189286.
## Iteration 16
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 125.852
## The bandwidth used in the last iteration is: 125.933 and the difference in bandwidths is: 0.0809201
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 254.549
## The bandwidth used in the last iteration is: 253.994 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 751.408
## The bandwidth used in the last iteration is: 747.607 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 803.521
## The bandwidth used in the last iteration is: 809.672 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 338.314
## The bandwidth used in the last iteration is: 338.314 and the difference in bandwidths is: 0
## The bandwidth for variable X4_hunian seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 16 change of RSS (dCVR) is 0.00766477.
## Iteration 17
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 125.721
## The bandwidth used in the last iteration is: 125.852 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 254.549
## The bandwidth used in the last iteration is: 254.549 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 761.361
## The bandwidth used in the last iteration is: 751.408 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 799.719
## The bandwidth used in the last iteration is: 803.521 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 338.314
## The bandwidth used in the last iteration is: 338.314 and the difference in bandwidths is: 0
## The bandwidth for variable X4_hunian seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 17 change of RSS (dCVR) is 0.0147348.
## Iteration 18
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 125.721
## The bandwidth used in the last iteration is: 125.721 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 254.549
## The bandwidth used in the last iteration is: 254.549 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 767.512
## The bandwidth used in the last iteration is: 761.361 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 799.719
## The bandwidth used in the last iteration is: 799.719 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 338.314
## The bandwidth used in the last iteration is: 338.314 and the difference in bandwidths is: 0
## The bandwidth for variable X4_hunian seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Iteration 18 change of RSS (dCVR) is 0.011479.
## Iteration 19
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 125.509
## The bandwidth used in the last iteration is: 125.721 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 255.447
## The bandwidth used in the last iteration is: 254.549 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 773.663
## The bandwidth used in the last iteration is: 767.512 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 795.917
## The bandwidth used in the last iteration is: 799.719 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 338.314
## The bandwidth used in the last iteration is: 338.314 and the difference in bandwidths is: 0
## The bandwidth for variable X4_hunian seems to be converged for 4 times. It will be continually optimized in the next 1 times
## Iteration 19 change of RSS (dCVR) is 0.010891.
## Iteration 20
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 125.378
## The bandwidth used in the last iteration is: 125.509 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 255.447
## The bandwidth used in the last iteration is: 255.447 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 779.814
## The bandwidth used in the last iteration is: 773.663 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 793.568
## The bandwidth used in the last iteration is: 795.917 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X4_hunian
## The newly selected bandwidth for variable: X4_hunian is 338.314
## The bandwidth used in the last iteration is: 338.314 and the difference in bandwidths is: 0
## The bandwidth for variable X4_hunian seems to be converged and will be kept the same in the following iterations.
## Iteration 20 change of RSS (dCVR) is 0.0166936.
## Iteration 21
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 125.297
## The bandwidth used in the last iteration is: 125.378 and the difference in bandwidths is: 0.0809201
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 255.447
## The bandwidth used in the last iteration is: 255.447 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 787.417
## The bandwidth used in the last iteration is: 779.814 and the difference in bandwidths is: 7.60305
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 789.766
## The bandwidth used in the last iteration is: 793.568 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 21 change of RSS (dCVR) is 0.0110917.
## Iteration 22
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 125.166
## The bandwidth used in the last iteration is: 125.297 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 255.447
## The bandwidth used in the last iteration is: 255.447 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 793.568
## The bandwidth used in the last iteration is: 787.417 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 789.766
## The bandwidth used in the last iteration is: 789.766 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 22 change of RSS (dCVR) is 0.0131154.
## Iteration 23
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.955
## The bandwidth used in the last iteration is: 125.166 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 257.796
## The bandwidth used in the last iteration is: 255.447 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 799.719
## The bandwidth used in the last iteration is: 793.568 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 783.616
## The bandwidth used in the last iteration is: 789.766 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 23 change of RSS (dCVR) is 0.0178998.
## Iteration 24
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.824
## The bandwidth used in the last iteration is: 124.955 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 256.899
## The bandwidth used in the last iteration is: 257.796 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 809.672
## The bandwidth used in the last iteration is: 799.719 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 783.616
## The bandwidth used in the last iteration is: 783.616 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 24 change of RSS (dCVR) is 0.0233953.
## Iteration 25
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.612
## The bandwidth used in the last iteration is: 124.824 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 256.344
## The bandwidth used in the last iteration is: 256.899 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 815.823
## The bandwidth used in the last iteration is: 809.672 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 783.616
## The bandwidth used in the last iteration is: 783.616 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 25 change of RSS (dCVR) is 0.0236322.
## Iteration 26
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.612
## The bandwidth used in the last iteration is: 124.612 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 256.899
## The bandwidth used in the last iteration is: 256.344 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 825.775
## The bandwidth used in the last iteration is: 815.823 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 779.814
## The bandwidth used in the last iteration is: 783.616 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 26 change of RSS (dCVR) is 0.0183396.
## Iteration 27
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.481
## The bandwidth used in the last iteration is: 124.612 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 256.344
## The bandwidth used in the last iteration is: 256.899 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 825.775
## The bandwidth used in the last iteration is: 825.775 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 779.814
## The bandwidth used in the last iteration is: 779.814 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 27 change of RSS (dCVR) is 0.0212393.
## Iteration 28
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.4
## The bandwidth used in the last iteration is: 124.481 and the difference in bandwidths is: 0.0809201
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 256.344
## The bandwidth used in the last iteration is: 256.344 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 835.728
## The bandwidth used in the last iteration is: 825.775 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 783.616
## The bandwidth used in the last iteration is: 779.814 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 28 change of RSS (dCVR) is 0.00926895.
## Iteration 29
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.269
## The bandwidth used in the last iteration is: 124.4 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 256.344
## The bandwidth used in the last iteration is: 256.344 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 841.879
## The bandwidth used in the last iteration is: 835.728 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 783.616
## The bandwidth used in the last iteration is: 783.616 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 29 change of RSS (dCVR) is 0.0133363.
## Iteration 30
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.269
## The bandwidth used in the last iteration is: 124.269 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 256.899
## The bandwidth used in the last iteration is: 256.344 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 851.831
## The bandwidth used in the last iteration is: 841.879 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 777.465
## The bandwidth used in the last iteration is: 783.616 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 30 change of RSS (dCVR) is 0.0166256.
## Iteration 31
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 124.057
## The bandwidth used in the last iteration is: 124.269 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 257.241
## The bandwidth used in the last iteration is: 256.899 and the difference in bandwidths is: 0.342783
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 851.831
## The bandwidth used in the last iteration is: 851.831 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 773.663
## The bandwidth used in the last iteration is: 777.465 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 31 change of RSS (dCVR) is 0.0202313.
## Iteration 32
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.714
## The bandwidth used in the last iteration is: 124.057 and the difference in bandwidths is: 0.342783
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 257.796
## The bandwidth used in the last iteration is: 257.241 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 867.935
## The bandwidth used in the last iteration is: 851.831 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 773.663
## The bandwidth used in the last iteration is: 773.663 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 32 change of RSS (dCVR) is 0.0205989.
## Iteration 33
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.926
## The bandwidth used in the last iteration is: 123.714 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 257.796
## The bandwidth used in the last iteration is: 257.796 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 867.935
## The bandwidth used in the last iteration is: 867.935 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 771.314
## The bandwidth used in the last iteration is: 773.663 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 33 change of RSS (dCVR) is 0.0223382.
## Iteration 34
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.795
## The bandwidth used in the last iteration is: 123.926 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 257.796
## The bandwidth used in the last iteration is: 257.796 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 877.887
## The bandwidth used in the last iteration is: 867.935 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 783.616
## The bandwidth used in the last iteration is: 771.314 and the difference in bandwidths is: 12.302
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 34 change of RSS (dCVR) is 0.0123506.
## Iteration 35
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.583
## The bandwidth used in the last iteration is: 123.795 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 258.693
## The bandwidth used in the last iteration is: 257.796 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 880.237
## The bandwidth used in the last iteration is: 877.887 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 773.663
## The bandwidth used in the last iteration is: 783.616 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 35 change of RSS (dCVR) is 0.0189968.
## Iteration 36
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.503
## The bandwidth used in the last iteration is: 123.583 and the difference in bandwidths is: 0.0809201
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 258.693
## The bandwidth used in the last iteration is: 258.693 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 884.038
## The bandwidth used in the last iteration is: 880.237 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 767.512
## The bandwidth used in the last iteration is: 773.663 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 36 change of RSS (dCVR) is 0.0162733.
## Iteration 37
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.372
## The bandwidth used in the last iteration is: 123.503 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 260.145
## The bandwidth used in the last iteration is: 258.693 and the difference in bandwidths is: 1.45205
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 890.189
## The bandwidth used in the last iteration is: 884.038 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 767.512
## The bandwidth used in the last iteration is: 767.512 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 37 change of RSS (dCVR) is 0.0171672.
## Iteration 38
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.714
## The bandwidth used in the last iteration is: 123.372 and the difference in bandwidths is: 0.342783
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 258.693
## The bandwidth used in the last iteration is: 260.145 and the difference in bandwidths is: 1.45205
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 893.991
## The bandwidth used in the last iteration is: 890.189 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 767.512
## The bandwidth used in the last iteration is: 767.512 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 38 change of RSS (dCVR) is 0.0201374.
## Iteration 39
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.372
## The bandwidth used in the last iteration is: 123.714 and the difference in bandwidths is: 0.342783
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 257.796
## The bandwidth used in the last iteration is: 258.693 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 936.15
## The bandwidth used in the last iteration is: 893.991 and the difference in bandwidths is: 42.1595
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 763.71
## The bandwidth used in the last iteration is: 767.512 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 39 change of RSS (dCVR) is 0.0237307.
## Iteration 40
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.372
## The bandwidth used in the last iteration is: 123.372 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 258.693
## The bandwidth used in the last iteration is: 257.796 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 913.896
## The bandwidth used in the last iteration is: 936.15 and the difference in bandwidths is: 22.2545
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 763.71
## The bandwidth used in the last iteration is: 763.71 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 40 change of RSS (dCVR) is 0.015535.
## Iteration 41
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.16
## The bandwidth used in the last iteration is: 123.372 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 259.248
## The bandwidth used in the last iteration is: 258.693 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 916.245
## The bandwidth used in the last iteration is: 913.896 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 767.512
## The bandwidth used in the last iteration is: 763.71 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 41 change of RSS (dCVR) is 0.0145368.
## Iteration 42
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 123.029
## The bandwidth used in the last iteration is: 123.16 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 259.248
## The bandwidth used in the last iteration is: 259.248 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 920.047
## The bandwidth used in the last iteration is: 916.245 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 767.512
## The bandwidth used in the last iteration is: 767.512 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 42 change of RSS (dCVR) is 0.017874.
## Iteration 43
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.948
## The bandwidth used in the last iteration is: 123.029 and the difference in bandwidths is: 0.0809201
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 259.248
## The bandwidth used in the last iteration is: 259.248 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 926.198
## The bandwidth used in the last iteration is: 920.047 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 757.559
## The bandwidth used in the last iteration is: 767.512 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X3_merokok will be continually selected in the next iteration.
## Iteration 43 change of RSS (dCVR) is 0.0181771.
## Iteration 44
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.817
## The bandwidth used in the last iteration is: 122.948 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 260.145
## The bandwidth used in the last iteration is: 259.248 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 932.349
## The bandwidth used in the last iteration is: 926.198 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 757.559
## The bandwidth used in the last iteration is: 757.559 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 44 change of RSS (dCVR) is 0.0101992.
## Iteration 45
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.817
## The bandwidth used in the last iteration is: 122.817 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 260.145
## The bandwidth used in the last iteration is: 260.145 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 936.15
## The bandwidth used in the last iteration is: 932.349 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 757.559
## The bandwidth used in the last iteration is: 757.559 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 45 change of RSS (dCVR) is 0.00667742.
## Iteration 46
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.605
## The bandwidth used in the last iteration is: 122.817 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 260.7
## The bandwidth used in the last iteration is: 260.145 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 942.301
## The bandwidth used in the last iteration is: 936.15 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 757.559
## The bandwidth used in the last iteration is: 757.559 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Iteration 46 change of RSS (dCVR) is 0.0156737.
## Iteration 47
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.605
## The bandwidth used in the last iteration is: 122.605 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 260.145
## The bandwidth used in the last iteration is: 260.7 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 946.103
## The bandwidth used in the last iteration is: 942.301 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 757.559
## The bandwidth used in the last iteration is: 757.559 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged for 4 times. It will be continually optimized in the next 1 times
## Iteration 47 change of RSS (dCVR) is 0.0119473.
## Iteration 48
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.474
## The bandwidth used in the last iteration is: 122.605 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 260.145
## The bandwidth used in the last iteration is: 260.145 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 952.254
## The bandwidth used in the last iteration is: 946.103 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X3_merokok
## The newly selected bandwidth for variable: X3_merokok is 757.559
## The bandwidth used in the last iteration is: 757.559 and the difference in bandwidths is: 0
## The bandwidth for variable X3_merokok seems to be converged and will be kept the same in the following iterations.
## Iteration 48 change of RSS (dCVR) is 0.014098.
## Iteration 49
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.474
## The bandwidth used in the last iteration is: 122.474 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 260.7
## The bandwidth used in the last iteration is: 260.145 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 962.206
## The bandwidth used in the last iteration is: 952.254 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 49 change of RSS (dCVR) is 0.0185916.
## Iteration 50
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.474
## The bandwidth used in the last iteration is: 122.474 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 260.145
## The bandwidth used in the last iteration is: 260.7 and the difference in bandwidths is: 0.554635
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 962.206
## The bandwidth used in the last iteration is: 962.206 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 50 change of RSS (dCVR) is 0.0115937.
## Iteration 51
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.262
## The bandwidth used in the last iteration is: 122.474 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 261.598
## The bandwidth used in the last iteration is: 260.145 and the difference in bandwidths is: 1.45205
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 968.357
## The bandwidth used in the last iteration is: 962.206 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 51 change of RSS (dCVR) is 0.00901216.
## Iteration 52
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.262
## The bandwidth used in the last iteration is: 122.262 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 261.598
## The bandwidth used in the last iteration is: 261.598 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 972.159
## The bandwidth used in the last iteration is: 968.357 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 52 change of RSS (dCVR) is 0.00297582.
## Iteration 53
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 122.131
## The bandwidth used in the last iteration is: 122.262 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 261.598
## The bandwidth used in the last iteration is: 261.598 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 978.31
## The bandwidth used in the last iteration is: 972.159 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 53 change of RSS (dCVR) is 0.0154179.
## Iteration 54
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.92
## The bandwidth used in the last iteration is: 122.131 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 262.495
## The bandwidth used in the last iteration is: 261.598 and the difference in bandwidths is: 0.897418
## The bandwidth for variable X1_miskin will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 988.262
## The bandwidth used in the last iteration is: 978.31 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 54 change of RSS (dCVR) is 0.010912.
## Iteration 55
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.92
## The bandwidth used in the last iteration is: 121.92 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 262.495
## The bandwidth used in the last iteration is: 262.495 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 988.262
## The bandwidth used in the last iteration is: 988.262 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 55 change of RSS (dCVR) is 0.0024174.
## Iteration 56
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.92
## The bandwidth used in the last iteration is: 121.92 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 262.495
## The bandwidth used in the last iteration is: 262.495 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 994.413
## The bandwidth used in the last iteration is: 988.262 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 56 change of RSS (dCVR) is 0.0102009.
## Iteration 57
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.92
## The bandwidth used in the last iteration is: 121.92 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 262.495
## The bandwidth used in the last iteration is: 262.495 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 994.413
## The bandwidth used in the last iteration is: 994.413 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 57 change of RSS (dCVR) is 0.00731194.
## Iteration 58
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.708
## The bandwidth used in the last iteration is: 121.92 and the difference in bandwidths is: 0.211852
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 262.495
## The bandwidth used in the last iteration is: 262.495 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged for 4 times. It will be continually optimized in the next 1 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1004.37
## The bandwidth used in the last iteration is: 994.413 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 58 change of RSS (dCVR) is 0.0203438.
## Iteration 59
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.708
## The bandwidth used in the last iteration is: 121.708 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X1_miskin
## The newly selected bandwidth for variable: X1_miskin is 262.495
## The bandwidth used in the last iteration is: 262.495 and the difference in bandwidths is: 0
## The bandwidth for variable X1_miskin seems to be converged and will be kept the same in the following iterations.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1010.52
## The bandwidth used in the last iteration is: 1004.37 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 59 change of RSS (dCVR) is 0.00953018.
## Iteration 60
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.708
## The bandwidth used in the last iteration is: 121.708 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1020.47
## The bandwidth used in the last iteration is: 1010.52 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 60 change of RSS (dCVR) is 0.0127043.
## Iteration 61
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.708
## The bandwidth used in the last iteration is: 121.708 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1020.47
## The bandwidth used in the last iteration is: 1020.47 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 61 change of RSS (dCVR) is 0.00873294.
## Iteration 62
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.577
## The bandwidth used in the last iteration is: 121.708 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1024.27
## The bandwidth used in the last iteration is: 1020.47 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 62 change of RSS (dCVR) is 0.0158888.
## Iteration 63
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.708
## The bandwidth used in the last iteration is: 121.577 and the difference in bandwidths is: 0.130932
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1026.62
## The bandwidth used in the last iteration is: 1024.27 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 63 change of RSS (dCVR) is 0.0200812.
## Iteration 64
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.708
## The bandwidth used in the last iteration is: 121.708 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1030.42
## The bandwidth used in the last iteration is: 1026.62 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 64 change of RSS (dCVR) is 0.0101429.
## Iteration 65
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.365
## The bandwidth used in the last iteration is: 121.708 and the difference in bandwidths is: 0.342783
## The bandwidth for variable Intercept will be continually selected in the next iteration.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1036.57
## The bandwidth used in the last iteration is: 1030.42 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 65 change of RSS (dCVR) is 0.0283709.
## Iteration 66
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.365
## The bandwidth used in the last iteration is: 121.365 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1040.37
## The bandwidth used in the last iteration is: 1036.57 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 66 change of RSS (dCVR) is 0.00570709.
## Iteration 67
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.365
## The bandwidth used in the last iteration is: 121.365 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1046.53
## The bandwidth used in the last iteration is: 1040.37 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 67 change of RSS (dCVR) is 0.00987665.
## Iteration 68
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.365
## The bandwidth used in the last iteration is: 121.365 and the difference in bandwidths is: 0
## The bandwidth for variable Intercept seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1050.33
## The bandwidth used in the last iteration is: 1046.53 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 68 change of RSS (dCVR) is 0.00928735.
## Iteration 69
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.284
## The bandwidth used in the last iteration is: 121.365 and the difference in bandwidths is: 0.0809201
## The bandwidth for variable Intercept seems to be converged for 4 times. It will be continually optimized in the next 1 times
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1052.68
## The bandwidth used in the last iteration is: 1050.33 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 69 change of RSS (dCVR) is 0.0120549.
## Iteration 70
## Now select an optimum bandwidth for the variable: Intercept
## The newly selected bandwidth for variable: Intercept is 121.365
## The bandwidth used in the last iteration is: 121.284 and the difference in bandwidths is: 0.0809201
## The bandwidth for variable Intercept seems to be converged and will be kept the same in the following iterations.
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1056.48
## The bandwidth used in the last iteration is: 1052.68 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 70 change of RSS (dCVR) is 0.0168147.
## Iteration 71
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1062.63
## The bandwidth used in the last iteration is: 1056.48 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 71 change of RSS (dCVR) is 0.0105623.
## Iteration 72
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1062.63
## The bandwidth used in the last iteration is: 1062.63 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 72 change of RSS (dCVR) is 0.00716639.
## Iteration 73
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1068.78
## The bandwidth used in the last iteration is: 1062.63 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 73 change of RSS (dCVR) is 0.00975226.
## Iteration 74
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1072.58
## The bandwidth used in the last iteration is: 1068.78 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 74 change of RSS (dCVR) is 0.00889185.
## Iteration 75
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1078.73
## The bandwidth used in the last iteration is: 1072.58 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 75 change of RSS (dCVR) is 0.00998911.
## Iteration 76
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1082.53
## The bandwidth used in the last iteration is: 1078.73 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 76 change of RSS (dCVR) is 0.00910533.
## Iteration 77
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1088.68
## The bandwidth used in the last iteration is: 1082.53 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 77 change of RSS (dCVR) is 0.0100581.
## Iteration 78
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1092.49
## The bandwidth used in the last iteration is: 1088.68 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 78 change of RSS (dCVR) is 0.00913396.
## Iteration 79
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1094.84
## The bandwidth used in the last iteration is: 1092.49 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 79 change of RSS (dCVR) is 0.00820837.
## Iteration 80
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1098.64
## The bandwidth used in the last iteration is: 1094.84 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 80 change of RSS (dCVR) is 0.0085702.
## Iteration 81
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1104.79
## The bandwidth used in the last iteration is: 1098.64 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 81 change of RSS (dCVR) is 0.00962209.
## Iteration 82
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1108.59
## The bandwidth used in the last iteration is: 1104.79 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 82 change of RSS (dCVR) is 0.00880506.
## Iteration 83
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1110.94
## The bandwidth used in the last iteration is: 1108.59 and the difference in bandwidths is: 2.34947
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 83 change of RSS (dCVR) is 0.00794514.
## Iteration 84
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1114.74
## The bandwidth used in the last iteration is: 1110.94 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 84 change of RSS (dCVR) is 0.00834952.
## Iteration 85
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1120.89
## The bandwidth used in the last iteration is: 1114.74 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 85 change of RSS (dCVR) is 0.00942089.
## Iteration 86
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1130.84
## The bandwidth used in the last iteration is: 1120.89 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 86 change of RSS (dCVR) is 0.0112025.
## Iteration 87
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1130.84
## The bandwidth used in the last iteration is: 1130.84 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 87 change of RSS (dCVR) is 0.00747233.
## Iteration 88
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1134.65
## The bandwidth used in the last iteration is: 1130.84 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 88 change of RSS (dCVR) is 0.0085093.
## Iteration 89
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1140.8
## The bandwidth used in the last iteration is: 1134.65 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 89 change of RSS (dCVR) is 0.00938783.
## Iteration 90
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1140.8
## The bandwidth used in the last iteration is: 1140.8 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 90 change of RSS (dCVR) is 0.00654853.
## Iteration 91
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1146.95
## The bandwidth used in the last iteration is: 1140.8 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 91 change of RSS (dCVR) is 0.00902745.
## Iteration 92
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1156.9
## The bandwidth used in the last iteration is: 1146.95 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 92 change of RSS (dCVR) is 0.010803.
## Iteration 93
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1156.9
## The bandwidth used in the last iteration is: 1156.9 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 93 change of RSS (dCVR) is 0.00717138.
## Iteration 94
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1156.9
## The bandwidth used in the last iteration is: 1156.9 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 94 change of RSS (dCVR) is 0.0061671.
## Iteration 95
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1156.9
## The bandwidth used in the last iteration is: 1156.9 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Iteration 95 change of RSS (dCVR) is 0.005178.
## Iteration 96
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1163.05
## The bandwidth used in the last iteration is: 1156.9 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 96 change of RSS (dCVR) is 0.00824819.
## Iteration 97
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1166.85
## The bandwidth used in the last iteration is: 1163.05 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 97 change of RSS (dCVR) is 0.00767536.
## Iteration 98
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1173
## The bandwidth used in the last iteration is: 1166.85 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 98 change of RSS (dCVR) is 0.00887696.
## Iteration 99
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1176.81
## The bandwidth used in the last iteration is: 1173 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 99 change of RSS (dCVR) is 0.00812272.
## Iteration 100
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1182.96
## The bandwidth used in the last iteration is: 1176.81 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 100 change of RSS (dCVR) is 0.00906978.
## Iteration 101
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1182.96
## The bandwidth used in the last iteration is: 1182.96 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 101 change of RSS (dCVR) is 0.00626838.
## Iteration 102
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1189.11
## The bandwidth used in the last iteration is: 1182.96 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 102 change of RSS (dCVR) is 0.00864536.
## Iteration 103
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1199.06
## The bandwidth used in the last iteration is: 1189.11 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 103 change of RSS (dCVR) is 0.010364.
## Iteration 104
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1199.06
## The bandwidth used in the last iteration is: 1199.06 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 104 change of RSS (dCVR) is 0.00683112.
## Iteration 105
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1199.06
## The bandwidth used in the last iteration is: 1199.06 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 105 change of RSS (dCVR) is 0.0058398.
## Iteration 106
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1199.06
## The bandwidth used in the last iteration is: 1199.06 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Iteration 106 change of RSS (dCVR) is 0.0048683.
## Iteration 107
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1209.01
## The bandwidth used in the last iteration is: 1199.06 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 107 change of RSS (dCVR) is 0.00946935.
## Iteration 108
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1209.01
## The bandwidth used in the last iteration is: 1209.01 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 108 change of RSS (dCVR) is 0.00586549.
## Iteration 109
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1215.16
## The bandwidth used in the last iteration is: 1209.01 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 109 change of RSS (dCVR) is 0.00839206.
## Iteration 110
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1215.16
## The bandwidth used in the last iteration is: 1215.16 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 110 change of RSS (dCVR) is 0.00559574.
## Iteration 111
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1225.12
## The bandwidth used in the last iteration is: 1215.16 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 111 change of RSS (dCVR) is 0.009678.
## Iteration 112
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1225.12
## The bandwidth used in the last iteration is: 1225.12 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 112 change of RSS (dCVR) is 0.00608584.
## Iteration 113
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1231.27
## The bandwidth used in the last iteration is: 1225.12 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 113 change of RSS (dCVR) is 0.00840147.
## Iteration 114
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1241.22
## The bandwidth used in the last iteration is: 1231.27 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 114 change of RSS (dCVR) is 0.0100165.
## Iteration 115
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1241.22
## The bandwidth used in the last iteration is: 1241.22 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 115 change of RSS (dCVR) is 0.00657876.
## Iteration 116
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1241.22
## The bandwidth used in the last iteration is: 1241.22 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 116 change of RSS (dCVR) is 0.00559265.
## Iteration 117
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1267.28
## The bandwidth used in the last iteration is: 1241.22 and the difference in bandwidths is: 26.056
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 117 change of RSS (dCVR) is 0.0140268.
## Iteration 118
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1257.32
## The bandwidth used in the last iteration is: 1267.28 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 118 change of RSS (dCVR) is 0.000718092.
## Iteration 119
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1251.17
## The bandwidth used in the last iteration is: 1257.32 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 119 change of RSS (dCVR) is 0.00332883.
## Iteration 120
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1267.28
## The bandwidth used in the last iteration is: 1251.17 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 120 change of RSS (dCVR) is 0.0106425.
## Iteration 121
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1267.28
## The bandwidth used in the last iteration is: 1267.28 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 121 change of RSS (dCVR) is 0.00602739.
## Iteration 122
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1267.28
## The bandwidth used in the last iteration is: 1267.28 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 122 change of RSS (dCVR) is 0.0053574.
## Iteration 123
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1277.23
## The bandwidth used in the last iteration is: 1267.28 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 123 change of RSS (dCVR) is 0.00918907.
## Iteration 124
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1277.23
## The bandwidth used in the last iteration is: 1277.23 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 124 change of RSS (dCVR) is 0.00576185.
## Iteration 125
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1283.38
## The bandwidth used in the last iteration is: 1277.23 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 125 change of RSS (dCVR) is 0.00802227.
## Iteration 126
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1283.38
## The bandwidth used in the last iteration is: 1283.38 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 126 change of RSS (dCVR) is 0.00535972.
## Iteration 127
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1293.33
## The bandwidth used in the last iteration is: 1283.38 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 127 change of RSS (dCVR) is 0.00917741.
## Iteration 128
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1293.33
## The bandwidth used in the last iteration is: 1293.33 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 128 change of RSS (dCVR) is 0.00576757.
## Iteration 129
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1299.48
## The bandwidth used in the last iteration is: 1293.33 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 129 change of RSS (dCVR) is 0.00794204.
## Iteration 130
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1309.43
## The bandwidth used in the last iteration is: 1299.48 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 130 change of RSS (dCVR) is 0.0094703.
## Iteration 131
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1309.43
## The bandwidth used in the last iteration is: 1309.43 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 131 change of RSS (dCVR) is 0.00619305.
## Iteration 132
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1309.43
## The bandwidth used in the last iteration is: 1309.43 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 132 change of RSS (dCVR) is 0.0052345.
## Iteration 133
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1319.39
## The bandwidth used in the last iteration is: 1309.43 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 133 change of RSS (dCVR) is 0.00889884.
## Iteration 134
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1319.39
## The bandwidth used in the last iteration is: 1319.39 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 134 change of RSS (dCVR) is 0.00556995.
## Iteration 135
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1319.39
## The bandwidth used in the last iteration is: 1319.39 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 135 change of RSS (dCVR) is 0.00480011.
## Iteration 136
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1335.49
## The bandwidth used in the last iteration is: 1319.39 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 136 change of RSS (dCVR) is 0.0105819.
## Iteration 137
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1335.49
## The bandwidth used in the last iteration is: 1335.49 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 137 change of RSS (dCVR) is 0.00627984.
## Iteration 138
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1335.49
## The bandwidth used in the last iteration is: 1335.49 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 138 change of RSS (dCVR) is 0.0053908.
## Iteration 139
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1345.44
## The bandwidth used in the last iteration is: 1335.49 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 139 change of RSS (dCVR) is 0.0087995.
## Iteration 140
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1361.55
## The bandwidth used in the last iteration is: 1345.44 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 140 change of RSS (dCVR) is 0.0110967.
## Iteration 141
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1361.55
## The bandwidth used in the last iteration is: 1361.55 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 141 change of RSS (dCVR) is 0.00700812.
## Iteration 142
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1361.55
## The bandwidth used in the last iteration is: 1361.55 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 142 change of RSS (dCVR) is 0.0058637.
## Iteration 143
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1361.55
## The bandwidth used in the last iteration is: 1361.55 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Iteration 143 change of RSS (dCVR) is 0.00474437.
## Iteration 144
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1377.65
## The bandwidth used in the last iteration is: 1361.55 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 144 change of RSS (dCVR) is 0.0102985.
## Iteration 145
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1377.65
## The bandwidth used in the last iteration is: 1377.65 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 145 change of RSS (dCVR) is 0.00615084.
## Iteration 146
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1387.6
## The bandwidth used in the last iteration is: 1377.65 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 146 change of RSS (dCVR) is 0.00908622.
## Iteration 147
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1377.65
## The bandwidth used in the last iteration is: 1387.6 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 147 change of RSS (dCVR) is 0.00450301.
## Iteration 148
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1403.71
## The bandwidth used in the last iteration is: 1377.65 and the difference in bandwidths is: 26.056
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 148 change of RSS (dCVR) is 0.0122584.
## Iteration 149
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1403.71
## The bandwidth used in the last iteration is: 1403.71 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 149 change of RSS (dCVR) is 0.0067908.
## Iteration 150
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1409.86
## The bandwidth used in the last iteration is: 1403.71 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 150 change of RSS (dCVR) is 0.00818449.
## Iteration 151
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1413.66
## The bandwidth used in the last iteration is: 1409.86 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 151 change of RSS (dCVR) is 0.00717455.
## Iteration 152
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1419.81
## The bandwidth used in the last iteration is: 1413.66 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 152 change of RSS (dCVR) is 0.00773386.
## Iteration 153
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1429.76
## The bandwidth used in the last iteration is: 1419.81 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 153 change of RSS (dCVR) is 0.00894067.
## Iteration 154
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1435.91
## The bandwidth used in the last iteration is: 1429.76 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 154 change of RSS (dCVR) is 0.00814312.
## Iteration 155
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1439.72
## The bandwidth used in the last iteration is: 1435.91 and the difference in bandwidths is: 3.80152
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 155 change of RSS (dCVR) is 0.00725834.
## Iteration 156
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1445.87
## The bandwidth used in the last iteration is: 1439.72 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 156 change of RSS (dCVR) is 0.00769931.
## Iteration 157
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1455.82
## The bandwidth used in the last iteration is: 1445.87 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 157 change of RSS (dCVR) is 0.00882631.
## Iteration 158
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1461.97
## The bandwidth used in the last iteration is: 1455.82 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 158 change of RSS (dCVR) is 0.00802154.
## Iteration 159
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1471.92
## The bandwidth used in the last iteration is: 1461.97 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 159 change of RSS (dCVR) is 0.00899161.
## Iteration 160
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1471.92
## The bandwidth used in the last iteration is: 1471.92 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 160 change of RSS (dCVR) is 0.00598675.
## Iteration 161
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1488.03
## The bandwidth used in the last iteration is: 1471.92 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 161 change of RSS (dCVR) is 0.0100812.
## Iteration 162
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1497.98
## The bandwidth used in the last iteration is: 1488.03 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 162 change of RSS (dCVR) is 0.00923172.
## Iteration 163
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1497.98
## The bandwidth used in the last iteration is: 1497.98 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 163 change of RSS (dCVR) is 0.00635361.
## Iteration 164
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1514.08
## The bandwidth used in the last iteration is: 1497.98 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 164 change of RSS (dCVR) is 0.0100598.
## Iteration 165
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1524.03
## The bandwidth used in the last iteration is: 1514.08 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 165 change of RSS (dCVR) is 0.00916418.
## Iteration 166
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1530.19
## The bandwidth used in the last iteration is: 1524.03 and the difference in bandwidths is: 6.15099
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 166 change of RSS (dCVR) is 0.0082146.
## Iteration 167
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1546.29
## The bandwidth used in the last iteration is: 1530.19 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 167 change of RSS (dCVR) is 0.0102704.
## Iteration 168
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1556.24
## The bandwidth used in the last iteration is: 1546.29 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 168 change of RSS (dCVR) is 0.00928139.
## Iteration 169
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1556.24
## The bandwidth used in the last iteration is: 1556.24 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 169 change of RSS (dCVR) is 0.00642865.
## Iteration 170
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1582.3
## The bandwidth used in the last iteration is: 1556.24 and the difference in bandwidths is: 26.056
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 170 change of RSS (dCVR) is 0.0117329.
## Iteration 171
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1598.4
## The bandwidth used in the last iteration is: 1582.3 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 171 change of RSS (dCVR) is 0.0107448.
## Iteration 172
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1608.35
## The bandwidth used in the last iteration is: 1598.4 and the difference in bandwidths is: 9.95252
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 172 change of RSS (dCVR) is 0.00962273.
## Iteration 173
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1624.46
## The bandwidth used in the last iteration is: 1608.35 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 173 change of RSS (dCVR) is 0.0104473.
## Iteration 174
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1640.56
## The bandwidth used in the last iteration is: 1624.46 and the difference in bandwidths is: 16.1035
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 174 change of RSS (dCVR) is 0.0104737.
## Iteration 175
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1692.67
## The bandwidth used in the last iteration is: 1640.56 and the difference in bandwidths is: 52.1121
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 175 change of RSS (dCVR) is 0.0156391.
## Iteration 176
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1692.67
## The bandwidth used in the last iteration is: 1692.67 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 176 change of RSS (dCVR) is 0.0092213.
## Iteration 177
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1692.67
## The bandwidth used in the last iteration is: 1692.67 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 177 change of RSS (dCVR) is 0.0074093.
## Iteration 178
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1734.83
## The bandwidth used in the last iteration is: 1692.67 and the difference in bandwidths is: 42.1595
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 178 change of RSS (dCVR) is 0.0134775.
## Iteration 179
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1760.89
## The bandwidth used in the last iteration is: 1734.83 and the difference in bandwidths is: 26.056
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 179 change of RSS (dCVR) is 0.0122632.
## Iteration 180
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1786.94
## The bandwidth used in the last iteration is: 1760.89 and the difference in bandwidths is: 26.056
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 180 change of RSS (dCVR) is 0.0122816.
## Iteration 181
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1829.1
## The bandwidth used in the last iteration is: 1786.94 and the difference in bandwidths is: 42.1595
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 181 change of RSS (dCVR) is 0.0140274.
## Iteration 182
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1871.26
## The bandwidth used in the last iteration is: 1829.1 and the difference in bandwidths is: 42.1595
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 182 change of RSS (dCVR) is 0.0142065.
## Iteration 183
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1897.32
## The bandwidth used in the last iteration is: 1871.26 and the difference in bandwidths is: 26.056
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 183 change of RSS (dCVR) is 0.0124401.
## Iteration 184
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 1955.58
## The bandwidth used in the last iteration is: 1897.32 and the difference in bandwidths is: 58.263
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 184 change of RSS (dCVR) is 0.0151172.
## Iteration 185
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 2007.69
## The bandwidth used in the last iteration is: 1955.58 and the difference in bandwidths is: 52.1121
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 185 change of RSS (dCVR) is 0.014734.
## Iteration 186
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 2092.01
## The bandwidth used in the last iteration is: 2007.69 and the difference in bandwidths is: 84.3191
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 186 change of RSS (dCVR) is 0.0169698.
## Iteration 187
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 2160.23
## The bandwidth used in the last iteration is: 2092.01 and the difference in bandwidths is: 68.2156
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 187 change of RSS (dCVR) is 0.0158567.
## Iteration 188
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 2254.5
## The bandwidth used in the last iteration is: 2160.23 and the difference in bandwidths is: 94.2716
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 188 change of RSS (dCVR) is 0.0169602.
## Iteration 189
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 2380.98
## The bandwidth used in the last iteration is: 2254.5 and the difference in bandwidths is: 126.479
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 189 change of RSS (dCVR) is 0.0182177.
## Iteration 190
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 2559.57
## The bandwidth used in the last iteration is: 2380.98 and the difference in bandwidths is: 178.591
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 190 change of RSS (dCVR) is 0.0198818.
## Iteration 191
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 2806.38
## The bandwidth used in the last iteration is: 2559.57 and the difference in bandwidths is: 246.806
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 191 change of RSS (dCVR) is 0.0212523.
## Iteration 192
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 3179.66
## The bandwidth used in the last iteration is: 2806.38 and the difference in bandwidths is: 373.285
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 192 change of RSS (dCVR) is 0.0228587.
## Iteration 193
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 3894.02
## The bandwidth used in the last iteration is: 3179.66 and the difference in bandwidths is: 714.363
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 193 change of RSS (dCVR) is 0.0256837.
## Iteration 194
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5160.26
## The bandwidth used in the last iteration is: 3894.02 and the difference in bandwidths is: 1266.24
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 194 change of RSS (dCVR) is 0.0260137.
## Iteration 195
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5182.52
## The bandwidth used in the last iteration is: 5160.26 and the difference in bandwidths is: 22.2545
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 195 change of RSS (dCVR) is 0.010086.
## Iteration 196
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5182.52
## The bandwidth used in the last iteration is: 5182.52 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 196 change of RSS (dCVR) is 0.00549882.
## Iteration 197
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5182.52
## The bandwidth used in the last iteration is: 5182.52 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 197 change of RSS (dCVR) is 0.00415451.
## Iteration 198
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5183.97
## The bandwidth used in the last iteration is: 5182.52 and the difference in bandwidths is: 1.45205
## The bandwidth for variable X2_sanitasi will be continually selected in the next iteration.
## Iteration 198 change of RSS (dCVR) is 0.00464529.
## Iteration 199
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5183.97
## The bandwidth used in the last iteration is: 5183.97 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 1 times. It will be continually optimized in the next 4 times
## Iteration 199 change of RSS (dCVR) is 0.00492195.
## Iteration 200
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5183.97
## The bandwidth used in the last iteration is: 5183.97 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 2 times. It will be continually optimized in the next 3 times
## Iteration 200 change of RSS (dCVR) is 0.00493549.
## Iteration 201
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5183.97
## The bandwidth used in the last iteration is: 5183.97 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 3 times. It will be continually optimized in the next 2 times
## Iteration 201 change of RSS (dCVR) is 0.00475254.
## Iteration 202
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5183.97
## The bandwidth used in the last iteration is: 5183.97 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged for 4 times. It will be continually optimized in the next 1 times
## Iteration 202 change of RSS (dCVR) is 0.00445174.
## Iteration 203
## Now select an optimum bandwidth for the variable: X2_sanitasi
## The newly selected bandwidth for variable: X2_sanitasi is 5183.97
## The bandwidth used in the last iteration is: 5183.97 and the difference in bandwidths is: 0
## The bandwidth for variable X2_sanitasi seems to be converged and will be kept the same in the following iterations.
## Iteration 203 change of RSS (dCVR) is 0.00407984.
## Iteration 204
## Iteration 204 change of RSS (dCVR) is 0.00366426.
## Iteration 205
## Iteration 205 change of RSS (dCVR) is 0.0032203.
## Iteration 206
## Iteration 206 change of RSS (dCVR) is 0.00275465.
## Iteration 207
## Iteration 207 change of RSS (dCVR) is 0.00226568.
## Iteration 208
## Iteration 208 change of RSS (dCVR) is 0.00173838.
## Iteration 209
## Iteration 209 change of RSS (dCVR) is 0.00111673.
## Iteration 210
## Iteration 210 change of RSS (dCVR) is 0.000460552.
## Iteration 211
## Iteration 211 change of RSS (dCVR) is 0.00117643.
## Iteration 212
## Iteration 212 change of RSS (dCVR) is 0.00151672.
## Iteration 213
## Iteration 213 change of RSS (dCVR) is 0.00173037.
## Iteration 214
## Iteration 214 change of RSS (dCVR) is 0.00187003.
## Iteration 215
## Iteration 215 change of RSS (dCVR) is 0.00195928.
## Iteration 216
## Iteration 216 change of RSS (dCVR) is 0.00201164.
## Iteration 217
## Iteration 217 change of RSS (dCVR) is 0.00203596.
## Iteration 218
## Iteration 218 change of RSS (dCVR) is 0.00203852.
## Iteration 219
## Iteration 219 change of RSS (dCVR) is 0.00202401.
## Iteration 220
## Iteration 220 change of RSS (dCVR) is 0.00199606.
## Iteration 221
## Iteration 221 change of RSS (dCVR) is 0.00195755.
## Iteration 222
## Iteration 222 change of RSS (dCVR) is 0.00191078.
## Iteration 223
## Iteration 223 change of RSS (dCVR) is 0.00185767.
## Iteration 224
## Iteration 224 change of RSS (dCVR) is 0.00179975.
## Iteration 225
## Iteration 225 change of RSS (dCVR) is 0.00173833.
## Iteration 226
## Iteration 226 change of RSS (dCVR) is 0.00167447.
## Iteration 227
## Iteration 227 change of RSS (dCVR) is 0.00160906.
## Iteration 228
## Iteration 228 change of RSS (dCVR) is 0.00154285.
## Iteration 229
## Iteration 229 change of RSS (dCVR) is 0.00147643.
## Iteration 230
## Iteration 230 change of RSS (dCVR) is 0.00141033.
## Iteration 231
## Iteration 231 change of RSS (dCVR) is 0.00134496.
## Iteration 232
## Iteration 232 change of RSS (dCVR) is 0.00128067.
## Iteration 233
## Iteration 233 change of RSS (dCVR) is 0.00121772.
## Iteration 234
## Iteration 234 change of RSS (dCVR) is 0.00115634.
## Iteration 235
## Iteration 235 change of RSS (dCVR) is 0.00109671.
## Iteration 236
## Iteration 236 change of RSS (dCVR) is 0.00103896.
## Iteration 237
## Iteration 237 change of RSS (dCVR) is 0.000983175.
## Iteration 238
## Iteration 238 change of RSS (dCVR) is 0.00092944.
## Iteration 239
## Iteration 239 change of RSS (dCVR) is 0.000877795.
## Iteration 240
## Iteration 240 change of RSS (dCVR) is 0.000828262.
## Iteration 241
## Iteration 241 change of RSS (dCVR) is 0.000780847.
## Iteration 242
## Iteration 242 change of RSS (dCVR) is 0.00073554.
## Iteration 243
## Iteration 243 change of RSS (dCVR) is 0.000692318.
## Iteration 244
## Iteration 244 change of RSS (dCVR) is 0.000651148.
## Iteration 245
## Iteration 245 change of RSS (dCVR) is 0.000611989.
## Iteration 246
## Iteration 246 change of RSS (dCVR) is 0.000574792.
## Iteration 247
## Iteration 247 change of RSS (dCVR) is 0.000539504.
## Iteration 248
## Iteration 248 change of RSS (dCVR) is 0.000506065.
## Iteration 249
## Iteration 249 change of RSS (dCVR) is 0.000474415.
## Iteration 250
## Iteration 250 change of RSS (dCVR) is 0.000444489.
## Iteration 251
## Iteration 251 change of RSS (dCVR) is 0.000416221.
## Iteration 252
## Iteration 252 change of RSS (dCVR) is 0.000389545.
## Iteration 253
## Iteration 253 change of RSS (dCVR) is 0.000364395.
## Iteration 254
## Iteration 254 change of RSS (dCVR) is 0.000340702.
## Iteration 255
## Iteration 255 change of RSS (dCVR) is 0.000318403.
## Iteration 256
## Iteration 256 change of RSS (dCVR) is 0.00029743.
## Iteration 257
## Iteration 257 change of RSS (dCVR) is 0.00027772.
## Iteration 258
## Iteration 258 change of RSS (dCVR) is 0.00025921.
## Iteration 259
## Iteration 259 change of RSS (dCVR) is 0.00024184.
## Iteration 260
## Iteration 260 change of RSS (dCVR) is 0.00022555.
## Iteration 261
## Iteration 261 change of RSS (dCVR) is 0.000210283.
## Iteration 262
## Iteration 262 change of RSS (dCVR) is 0.000195984.
## Iteration 263
## Iteration 263 change of RSS (dCVR) is 0.000182598.
## Iteration 264
## Iteration 264 change of RSS (dCVR) is 0.000170075.
## Iteration 265
## Iteration 265 change of RSS (dCVR) is 0.000158366.
## Iteration 266
## Iteration 266 change of RSS (dCVR) is 0.000147424.
## Iteration 267
## Iteration 267 change of RSS (dCVR) is 0.000137203.
## Iteration 268
## Iteration 268 change of RSS (dCVR) is 0.000127661.
## Iteration 269
## Iteration 269 change of RSS (dCVR) is 0.000118756.
## Iteration 270
## Iteration 270 change of RSS (dCVR) is 0.000110451.
## Iteration 271
## Iteration 271 change of RSS (dCVR) is 0.000102708.
## Iteration 272
## Iteration 272 change of RSS (dCVR) is 9.54922e-05.
## Iteration 273
## Iteration 273 change of RSS (dCVR) is 8.877e-05.
## Iteration 274
## Iteration 274 change of RSS (dCVR) is 8.25104e-05.
## Iteration 275
## Iteration 275 change of RSS (dCVR) is 7.66835e-05.
## Iteration 276
## Iteration 276 change of RSS (dCVR) is 7.12613e-05.
## Iteration 277
## Iteration 277 change of RSS (dCVR) is 6.62174e-05.
## Iteration 278
## Iteration 278 change of RSS (dCVR) is 6.15268e-05.
## Iteration 279
## Iteration 279 change of RSS (dCVR) is 5.71661e-05.
## Iteration 280
## Iteration 280 change of RSS (dCVR) is 5.31132e-05.
## Iteration 281
## Iteration 281 change of RSS (dCVR) is 4.93473e-05.
## Iteration 282
## Iteration 282 change of RSS (dCVR) is 4.58489e-05.
## Iteration 283
## Iteration 283 change of RSS (dCVR) is 4.25998e-05.
## Iteration 284
## Iteration 284 change of RSS (dCVR) is 3.95827e-05.
## Iteration 285
## Iteration 285 change of RSS (dCVR) is 3.67815e-05.
## Iteration 286
## Iteration 286 change of RSS (dCVR) is 3.41813e-05.
## Iteration 287
## Iteration 287 change of RSS (dCVR) is 3.1768e-05.
## Iteration 288
## Iteration 288 change of RSS (dCVR) is 2.95282e-05.
## Iteration 289
## Iteration 289 change of RSS (dCVR) is 2.74499e-05.
## Iteration 290
## Iteration 290 change of RSS (dCVR) is 2.55214e-05.
## Iteration 291
## Iteration 291 change of RSS (dCVR) is 2.37321e-05.
## Iteration 292
## Iteration 292 change of RSS (dCVR) is 2.2072e-05.
## Iteration 293
## Iteration 293 change of RSS (dCVR) is 2.05316e-05.
## Iteration 294
## Iteration 294 change of RSS (dCVR) is 1.91025e-05.
## Iteration 295
## Iteration 295 change of RSS (dCVR) is 1.77764e-05.
## Iteration 296
## Iteration 296 change of RSS (dCVR) is 1.65459e-05.
## Iteration 297
## Iteration 297 change of RSS (dCVR) is 1.54039e-05.
## Iteration 298
## Iteration 298 change of RSS (dCVR) is 1.43441e-05.
## Iteration 299
## Iteration 299 change of RSS (dCVR) is 1.33603e-05.
## Iteration 300
## Iteration 300 change of RSS (dCVR) is 1.2447e-05.
## Iteration 301
## Iteration 301 change of RSS (dCVR) is 1.1599e-05.
## Iteration 302
## Iteration 302 change of RSS (dCVR) is 1.08114e-05.
## Iteration 303
## Iteration 303 change of RSS (dCVR) is 1.00798e-05.
## Iteration 304
## Iteration 304 change of RSS (dCVR) is 9.40014e-06.
save_txt(MGWR, "28_MGWR_summary.txt")
saveRDS(MGWR, file.path(OUT, "28_MGWR_object.rds"))
# ---------------------- BAGIAN KODE 14 ----------------------
BW_FINAL <- MGWR$GW.arguments$bws
if(is.null(BW_FINAL)) BW_FINAL <- MGWR$bws.vars
if(is.null(BW_FINAL)) stop("Bandwidth tidak ditemukan. Jalankan str(MGWR$GW.arguments).")
BW_TABLE <- data.frame(
parameter = c("Intercept", xvars),
bandwidth = as.numeric(BW_FINAL)
)
BW_TABLE$persen_dari_n <- round(100 * BW_TABLE$bandwidth / n, 1)
write.csv(BW_TABLE, file.path(OUT, "29_MGWR_bandwidth.csv"), row.names = FALSE)
print(BW_TABLE)
## parameter bandwidth persen_dari_n
## 1 Intercept 121.3649 23.6
## 2 X1_miskin 262.4950 51.1
## 3 X2_sanitasi 5183.9682 1008.6
## 4 X3_merokok 757.5595 147.4
## 5 X4_hunian 338.3136 65.8
if(length(unique(round(BW_TABLE$bandwidth, 3))) == 1){
warning("Semua bandwidth MGWR sama. Periksa konvergensi/pengaturan bw.seled.")
}
# ---------------------- BAGIAN KODE 15 ----------------------
MGWR_DF <- as.data.frame(MGWR$SDF)
MGWR_DF$id <- mdat$id; MGWR_DF$wilayah <- mdat$wilayah
write.csv(MGWR_DF, file.path(OUT, "30_MGWR_all_local_results.csv"), row.names = FALSE)
writeLines(names(MGWR_DF), file.path(OUT, "31_MGWR_columns.txt"))
local_table <- data.frame(id = mdat$id, wilayah = mdat$wilayah)
sig_rows <- list()
for(v in xvars){
c_col <- find_col(MGWR_DF, v)
se_col <- find_col(MGWR_DF, c(paste0(v, "_SE"), paste0(v, ".SE")))
t_col <- find_col(MGWR_DF, c(paste0(v, "_TV"), paste0(v, ".TV"), paste0(v, "_t")))
if(is.na(c_col)) stop("Kolom koefisien ", v, " tidak ditemukan. Lihat 31_MGWR_columns.txt")
b <- MGWR_DF[[c_col]]
tv <- if(!is.na(t_col)) MGWR_DF[[t_col]] else if(!is.na(se_col)) b / MGWR_DF[[se_col]] else rep(NA_real_, n)
if(all(is.na(tv))) warning("t-value untuk ", v, " tidak tersedia; signifikansi tidak dapat dihitung.")
# P-value dua sisi berbasis pendekatan normal untuk statistik t lokal
p_raw <- 2 * pnorm(-abs(tv))
p_raw[!is.finite(p_raw)] <- NA_real_
sig <- abs(tv) > T_CRIT
local_table[[paste0(v, "_coef")]] <- b
local_table[[paste0(v, "_t")]] <- tv
local_table[[paste0(v, "_p_raw")]] <- p_raw
local_table[[paste0(v, "_sig")]] <- sig
local_table[[paste0(v, "_coef_sig")]] <- ifelse(sig, b, NA_real_)
sig_rows[[v]] <- data.frame(
variable = v,
bandwidth = BW_TABLE$bandwidth[BW_TABLE$parameter == v],
coef_min = min(b, na.rm = TRUE), coef_Q1 = unname(quantile(b, .25, na.rm = TRUE)),
coef_median = median(b, na.rm = TRUE), coef_mean = mean(b, na.rm = TRUE),
coef_Q3 = unname(quantile(b, .75, na.rm = TRUE)), coef_max = max(b, na.rm = TRUE),
n_sig_uncorrected = sum(sig, na.rm = TRUE),
n_sig_positif_uncorrected = sum(sig & b > 0, na.rm = TRUE),
n_sig_negatif_uncorrected = sum(sig & b < 0, na.rm = TRUE),
persen_sig_uncorrected = round(100 * mean(sig, na.rm = TRUE), 1),
n_sig_t1645 = sum(abs(tv) > 1.645, na.rm = TRUE),
n_sig_t2576 = sum(abs(tv) > 2.576, na.rm = TRUE)
)
}
# Koreksi Benjamini-Hochberg per variabel (FDR 5%)
# Setiap variabel dikoreksi atas 514 pengujian lokalnya masing-masing.
for(v in xvars){
p_raw <- local_table[[paste0(v, "_p_raw")]]
p_adj <- rep(NA_real_, length(p_raw))
valid_p <- is.finite(p_raw)
p_adj[valid_p] <- p.adjust(p_raw[valid_p], method = "BH")
local_table[[paste0(v, "_p_BH")]] <- p_adj
local_table[[paste0(v, "_sig_BH")]] <- !is.na(p_adj) & p_adj < 0.05
local_table[[paste0(v, "_coef_sig_BH")]] <- ifelse(
local_table[[paste0(v, "_sig_BH")]],
local_table[[paste0(v, "_coef")]], NA_real_
)
}
sig_table <- do.call(rbind, lapply(xvars, function(v){
b <- local_table[[paste0(v, "_coef")]]
tv <- local_table[[paste0(v, "_t")]]
sig_bh <- local_table[[paste0(v, "_sig_BH")]]
data.frame(
variable = v,
bandwidth = BW_TABLE$bandwidth[BW_TABLE$parameter == v],
coef_min = min(b, na.rm = TRUE), coef_Q1 = unname(quantile(b, .25, na.rm = TRUE)),
coef_median = median(b, na.rm = TRUE), coef_mean = mean(b, na.rm = TRUE),
coef_Q3 = unname(quantile(b, .75, na.rm = TRUE)), coef_max = max(b, na.rm = TRUE),
n_sig_BH = sum(sig_bh, na.rm = TRUE),
n_sig_positif_BH = sum(sig_bh & b > 0, na.rm = TRUE),
n_sig_negatif_BH = sum(sig_bh & b < 0, na.rm = TRUE),
persen_sig_BH = round(100 * mean(sig_bh, na.rm = TRUE), 1),
n_sig_t1645 = sum(abs(tv) > 1.645, na.rm = TRUE),
n_sig_t2576 = sum(abs(tv) > 2.576, na.rm = TRUE)
)
}))
write.csv(local_table, file.path(OUT, "32_MGWR_coef_t_signifikansi.csv"), row.names = FALSE)
write.csv(sig_table, file.path(OUT, "33_MGWR_ringkasan_koefisien.csv"), row.names = FALSE)
print(sig_table, digits = 3)
## variable bandwidth coef_min coef_Q1 coef_median coef_mean coef_Q3 coef_max
## 1 X1_miskin 262 -0.794 -0.5371 -0.382 -0.423 -0.314 -0.0849
## 2 X2_sanitasi 5184 -0.179 -0.1766 -0.173 -0.172 -0.169 -0.1596
## 3 X3_merokok 758 -0.356 -0.3303 -0.278 -0.255 -0.206 0.0352
## 4 X4_hunian 338 -0.138 -0.0331 0.080 0.124 0.192 0.6796
## n_sig_BH n_sig_positif_BH n_sig_negatif_BH persen_sig_BH n_sig_t1645
## 1 471 0 471 91.6 482
## 2 514 0 514 100.0 514
## 3 471 0 471 91.6 474
## 4 92 92 0 17.9 153
## n_sig_t2576
## 1 448
## 2 0
## 3 466
## 4 93
# ---------------------- BAGIAN KODE 16 ----------------------
res_col_m <- find_col(MGWR_DF, "residual")
fit_col_m <- find_col(MGWR_DF, c("yhat", "fitted"))
MGWR_RESID <- if(!is.na(res_col_m)) MGWR_DF[[res_col_m]] else
if(!is.na(fit_col_m)) mdat$Y_model - MGWR_DF[[fit_col_m]] else rep(NA_real_, n)
GWR_RESID <- if(!is.na(res_col_g)) GWR_DF[[res_col_g]] else rep(NA_real_, n)
if(all(is.finite(MGWR_RESID))){
save_txt(moran.test(MGWR_RESID, listw_knn, randomisation = TRUE,
alternative = "two.sided", zero.policy = TRUE), "34_Moran_MGWR_residual.txt")
}
# ---------------------- BAGIAN KODE 17 ----------------------
GWR_DIAG <- GWR$GW.diagnostic
MGWR_DIAG <- MGWR$GW.diagnostic
writeLines(capture.output(str(GWR_DIAG)), file.path(OUT, "35_GWR_diag_structure.txt"))
writeLines(capture.output(str(MGWR_DIAG)), file.path(OUT, "36_MGWR_diag_structure.txt"))
tss <- sum((mdat$Y_model - mean(mdat$Y_model))^2)
rmse_fun <- function(r) {
r <- as.numeric(r)
if (!length(r) || any(!is.finite(r))) return(NA_real_)
sqrt(mean(r^2))
}
rss_fun <- function(r) {
r <- as.numeric(r)
if (!length(r) || any(!is.finite(r))) return(NA_real_)
sum(r^2)
}
res_ols <- as.numeric(residuals(OLS))
rss_ols <- rss_fun(res_ols)
rss_g <- rss_fun(GWR_RESID)
rss_m <- rss_fun(MGWR_RESID)
comparison <- data.frame(
model = c("OLS", "GWR", "MGWR"),
AICc = c(AICc_OLS, get_stat(GWR_DIAG, "AICc"), get_stat(MGWR_DIAG, "AICc")),
R2 = c(if(is.finite(rss_ols)) 1 - rss_ols/tss else NA_real_,
if(is.finite(rss_g)) 1 - rss_g/tss else NA_real_,
if(is.finite(rss_m)) 1 - rss_m/tss else NA_real_),
Adj_R2 = c(summary(OLS)$adj.r.squared,
get_stat(GWR_DIAG, c("gwR2.adj", "R2adj")),
get_stat(MGWR_DIAG, c("gwR2.adj", "R2adj"))),
RSS = c(rss_ols, rss_g, rss_m),
RMSE_standardized_or_model_scale = c(rmse_fun(res_ols), rmse_fun(GWR_RESID), rmse_fun(MGWR_RESID))
)
writeLines(
"Catatan: RMSE pada tabel berada pada skala respons model. Karena STANDARDIZE=TRUE, nilai ini berada pada skala Y terstandarisasi, bukan TB rate asli.",
file.path(OUT, "37a_catatan_RMSE.txt")
)
write.csv(comparison, file.path(OUT, "37_perbandingan_model.csv"), row.names = FALSE)
print(comparison, digits = 4)
## model AICc R2 Adj_R2 RSS RMSE_standardized_or_model_scale
## 1 OLS 1459 0.02052 0.01282 502.5 0.9887
## 2 GWR 1260 0.51863 0.38500 246.9 0.6931
## 3 MGWR 1231 0.54583 0.41573 233.0 0.6733
# RMSE pada skala TB rate asli dihitung dari fitted values yang tersedia.
fit_ols_original <- if (STANDARDIZE) {
as.numeric(fitted(OLS)) * sd(data$Y_TB) + mean(data$Y_TB)
} else as.numeric(fitted(OLS))
fit_gwr_model <- mdat$Y_model - as.numeric(GWR_RESID)
fit_mgwr_model <- mdat$Y_model - as.numeric(MGWR_RESID)
if (Y_TRANSFORM == "raw") {
fit_gwr_original <- if (STANDARDIZE) fit_gwr_model * sd(data$Y_TB) + mean(data$Y_TB) else fit_gwr_model
fit_mgwr_original <- if (STANDARDIZE) fit_mgwr_model * sd(data$Y_TB) + mean(data$Y_TB) else fit_mgwr_model
rmse_original <- data.frame(
model = c("OLS", "GWR", "MGWR"),
RMSE_TB_rate_original_scale = c(
sqrt(mean((data$Y_TB - fit_ols_original)^2, na.rm = TRUE)),
sqrt(mean((data$Y_TB - fit_gwr_original)^2, na.rm = TRUE)),
sqrt(mean((data$Y_TB - fit_mgwr_original)^2, na.rm = TRUE))
)
)
write.csv(rmse_original, file.path(OUT, "37b_RMSE_skala_TB_asli.csv"), row.names = FALSE)
} else {
writeLines("RMSE skala TB asli tidak dihitung otomatis karena Y_TRANSFORM='log'; lakukan back-transform dengan mempertimbangkan bias retransformation.",
file.path(OUT, "37b_RMSE_skala_TB_asli.txt"))
}
# ---------------------- BAGIAN KODE 18 ----------------------
poly_result <- left_join(analysis_poly, local_table, by = c("id", "wilayah"))
poly_result$resid_MGWR <- MGWR_RESID
st_write(poly_result, file.path(OUT, "38_MGWR_polygon_results.gpkg"),
delete_dsn = TRUE, quiet = TRUE)
# ---------------------- BAGIAN KODE 19 ----------------------
cat("\n================ ANALISIS SELESAI ================\n")
##
## ================ ANALISIS SELESAI ================
cat("n =", n, "| Y:", Y_TRANSFORM, "| Standardisasi:", STANDARDIZE, "\n")
## n = 514 | Y: raw | Standardisasi: TRUE
cat("Kernel:", KERNEL, "| Bandwidth GWR:", BW_GWR, "| Mode bandwidth:", if (ADAPTIVE) "adaptive" else "fixed", "\n")
## Kernel: exponential | Bandwidth GWR: 235.5415 | Mode bandwidth: fixed
print(BW_TABLE); print(comparison, digits = 4)
## parameter bandwidth persen_dari_n
## 1 Intercept 121.3649 23.6
## 2 X1_miskin 262.4950 51.1
## 3 X2_sanitasi 5183.9682 1008.6
## 4 X3_merokok 757.5595 147.4
## 5 X4_hunian 338.3136 65.8
## model AICc R2 Adj_R2 RSS RMSE_standardized_or_model_scale
## 1 OLS 1459 0.02052 0.01282 502.5 0.9887
## 2 GWR 1260 0.51863 0.38500 246.9 0.6931
## 3 MGWR 1231 0.54583 0.41573 233.0 0.6733
cat("Hasil di folder:", OUT, "\n")
## Hasil di folder: hasil_MGWR_TBC_fixed
writeLines(capture.output(sessionInfo()), file.path(OUT, "39_sessionInfo.txt"))
# ---------------------- BAGIAN KODE 20 ----------------------
# PETA KOMBINASI VARIABEL SIGNIFIKAN DAN PERSAMAAN LOKAL MGWR
if (length(BW_FINAL) != length(xvars) + 1L ||
any(!is.finite(BW_FINAL)) || any(BW_FINAL <= 0)) {
stop("Bandwidth MGWR tidak valid untuk menghitung R-square lokal evaluatif.")
}
BW_EVAL_R2 <- median(as.numeric(BW_FINAL[-1]))
if (!is.finite(BW_EVAL_R2) || BW_EVAL_R2 <= 0) {
stop("Bandwidth evaluasi R-square lokal tidak valid.")
}
# Matriks jarak antartitik dalam kilometer.
dist_matrix_km <- sp::spDists(xy, longlat = TRUE)
# Bobot exponential fixed bandwidth: w_ij = exp(-d_ij / h_eval).
weight_matrix <- exp(-dist_matrix_km / BW_EVAL_R2)
y_eval <- as.numeric(mdat$Y_model)
yhat_eval <- as.numeric(MGWR_DF[[find_col(MGWR_DF, c("yhat", "fitted"))]])
if (length(yhat_eval) != n || any(!is.finite(y_eval)) ||
any(!is.finite(yhat_eval))) {
stop("Nilai aktual atau prediksi MGWR tidak lengkap untuk menghitung R-square lokal.")
}
local_r2_eval <- vapply(seq_len(n), function(i) {
w <- weight_matrix[i, ]
sw <- sum(w)
if (!is.finite(sw) || sw <= 0) return(NA_real_)
ybar_w <- sum(w * y_eval) / sw
sse_w <- sum(w * (y_eval - yhat_eval)^2)
sst_w <- sum(w * (y_eval - ybar_w)^2)
if (!is.finite(sst_w) || sst_w <= 0) return(NA_real_)
1 - sse_w / sst_w
}, numeric(1))
local_table$R2_lokal_evaluatif <- local_r2_eval
local_table$bandwidth_evaluasi_R2_km <- BW_EVAL_R2
if (all(is.na(local_table$R2_lokal_evaluatif))) {
stop("Seluruh R-square lokal evaluatif bernilai NA. Periksa koordinat dan data.")
}
# Simpan dokumentasi definisi dan parameter R-square lokal evaluatif.
r2_note <- c(
"R-square lokal evaluatif berbobot berbasis prediksi MGWR.",
"Bukan Local R-square bawaan GWmodel::gwr.multiscale.",
"Rumus: 1 - [sum_j w_ij (y_j - yhat_j)^2] / [sum_j w_ij (y_j - ybar_iw)^2].",
paste0("Bobot: w_ij = exp(-d_ij / h); kernel exponential fixed."),
paste0("Bandwidth evaluasi h = median bandwidth empat prediktor MGWR = ",
signif(BW_EVAL_R2, 8), " km."),
"Jarak dihitung menggunakan sp::spDists(..., longlat=TRUE), dalam kilometer.",
"Y dan yhat berada pada skala respons model yang digunakan saat estimasi MGWR.",
"Nilai dapat negatif jika kesalahan prediksi lokal berbobot melebihi variasi lokal berbobot.",
"Interpretasikan sebagai ukuran kecocokan lokal evaluatif untuk pengurutan, bukan sebagai diagnostik Local R2 resmi GWmodel."
)
writeLines(r2_note, file.path(OUT, "40a_definisi_R2_lokal_evaluatif.txt"))
write.csv(
data.frame(id = local_table$id, wilayah = local_table$wilayah,
R2_lokal_evaluatif = local_table$R2_lokal_evaluatif,
bandwidth_evaluasi_R2_km = BW_EVAL_R2),
file.path(OUT, "40b_R2_lokal_evaluatif.csv"),
row.names = FALSE
)
# Persamaan lokal: bintang diberikan jika koefisien signifikan setelah BH
intercept_col <- find_col(MGWR_DF, c("(Intercept)", "Intercept", "intercept"))
if (is.na(intercept_col)) stop("Kolom intersep MGWR tidak ditemukan.")
fmt_coef <- function(x) formatC(x, format = "f", digits = 4)
equations <- character(nrow(local_table))
for (i in seq_len(nrow(local_table))) {
b0 <- as.numeric(MGWR_DF[[intercept_col]][i])
terms <- vapply(seq_along(xvars), function(j) {
v <- xvars[j]
b <- as.numeric(local_table[[paste0(v, "_coef")]][i])
sg <- isTRUE(local_table[[paste0(v, "_sig_BH")]][i])
paste0(ifelse(b >= 0, "+", "-"),
fmt_coef(abs(b)), ifelse(sg, "*", ""), " ", paste0("X", j))
}, character(1))
equations[i] <- paste0("Yhat = ", fmt_coef(b0), " ",
paste(terms, collapse = " "))
}
local_table$persamaan_MGWR <- equations
# Label kombinasi signifikan
sig_cols <- paste0(xvars, "_sig_BH")
local_table$kombinasi <- apply(local_table[, sig_cols, drop = FALSE], 1, function(z) {
idx <- which(as.logical(z))
if (!length(idx)) "Tidak ada variabel signifikan"
else paste0("X", idx, collapse = ", ")
})
# Ringkasan jumlah wilayah untuk setiap kombinasi
kombinasi_table <- as.data.frame(table(local_table$kombinasi), stringsAsFactors = FALSE)
names(kombinasi_table) <- c("Kombinasi", "Jumlah_wilayah")
kombinasi_table$Persentase <- round(100 * kombinasi_table$Jumlah_wilayah / nrow(local_table), 2)
kombinasi_table <- kombinasi_table[order(-kombinasi_table$Jumlah_wilayah), ]
write.csv(kombinasi_table, file.path(OUT, "40_kombinasi_signifikansi_MGWR.csv"), row.names = FALSE)
# Tabel persamaan diurutkan berdasarkan R-square lokal evaluatif tertinggi.
persamaan_table <- local_table[, c(
"id", "wilayah", "R2_lokal_evaluatif",
"bandwidth_evaluasi_R2_km", "kombinasi", "persamaan_MGWR"
)]
persamaan_table <- persamaan_table[
order(-persamaan_table$R2_lokal_evaluatif, na.last = TRUE),
]
write.csv(
persamaan_table,
file.path(OUT, "41_persamaan_lokal_MGWR_urut_R2.csv"),
row.names = FALSE
)
# Peta kombinasi variabel signifikan
poly_result <- left_join(analysis_poly,
local_table[, c("id", "wilayah", "kombinasi")],
by = c("id", "wilayah"))
lev <- kombinasi_table$Kombinasi
poly_result$kombinasi <- factor(poly_result$kombinasi, levels = lev)
p_komb <- ggplot(poly_result) +
geom_sf(aes(fill = kombinasi), color = "white", linewidth = 0.025) +
scale_fill_viridis_d(
option = "C",
direction = 1,
drop = FALSE
) +
theme_void() +
labs(title = "Peta Kombinasi Variabel Signifikan MGWR",
subtitle = paste0("Kernel: ", KERNEL,
" | Koreksi BH per variabel (FDR 5%)"),
fill = "Kombinasi variabel") +
theme(plot.title = element_text(face = "bold"),
plot.subtitle = element_text(size = 8),
legend.position = "right")
ggsave(file.path(MAP, "Peta_Kombinasi_Variabel_Signifikan_MGWR.png"),
p_komb, width = 12, height = 6, dpi = 300)
st_write(poly_result, file.path(OUT, "42_peta_kombinasi_MGWR.gpkg"),
delete_dsn = TRUE, quiet = TRUE)
cat("\\nVisualisasi utama tersimpan di:", MAP, "\\n")
## \nVisualisasi utama tersimpan di: hasil_MGWR_TBC_fixed/peta \n
cat("Persamaan lokal terurut berdasarkan R-square MGWR tersimpan di:",
file.path(OUT, "41_persamaan_lokal_MGWR_urut_R2.csv"), "\\n")
## Persamaan lokal terurut berdasarkan R-square MGWR tersimpan di: hasil_MGWR_TBC_fixed/41_persamaan_lokal_MGWR_urut_R2.csv \n
cat("Kombinasi signifikansi tersimpan di:",
file.path(OUT, "40_kombinasi_signifikansi_MGWR.csv"), "\\n")
## Kombinasi signifikansi tersimpan di: hasil_MGWR_TBC_fixed/40_kombinasi_signifikansi_MGWR.csv \n
# ============================================================
# BAGIAN KODE 21
# TRANSFORMASI KOEFISIEN MGWR KE SKALA ASLI
# ============================================================
if (Y_TRANSFORM != "raw") {
stop("Kode ini menggunakan Y skala asli (Y_TRANSFORM = 'raw').")
}
# Statistik variabel asli
mean_Y <- mean(data$Y_TB, na.rm = TRUE)
sd_Y <- sd(data$Y_TB, na.rm = TRUE)
mean_X <- sapply(data[xvars], mean, na.rm = TRUE)
sd_X <- sapply(data[xvars], sd, na.rm = TRUE)
# Mengambil kolom intersep MGWR
intercept_col <- find_col(
MGWR_DF,
c("(Intercept)", "Intercept", "intercept")
)
if (is.na(intercept_col)) {
stop("Kolom intersep MGWR tidak ditemukan.")
}
# Membuat tabel koefisien skala asli
MGWR_ASLI <- data.frame(
id = MGWR_DF$id,
wilayah = MGWR_DF$wilayah
)
# Mengambil koefisien intersep dan prediktor
b0_std <- as.numeric(MGWR_DF[[intercept_col]])
beta_asli <- matrix(
NA_real_,
nrow = nrow(MGWR_DF),
ncol = length(xvars)
)
for (j in seq_along(xvars)) {
v <- xvars[j]
kolom <- find_col(MGWR_DF, v)
if (is.na(kolom)) {
stop("Koefisien tidak ditemukan: ", v)
}
b_std <- as.numeric(MGWR_DF[[kolom]])
beta_asli[, j] <- b_std * sd_Y / sd_X[j]
MGWR_ASLI[[paste0(v, "_coef_asli")]] <- beta_asli[, j]
}
# Transformasi intersep
MGWR_ASLI$Intercept_asli <-
mean_Y + sd_Y * b0_std -
as.numeric(beta_asli %*% mean_X)
# Fungsi format koefisien
fmt_asli <- function(x) {
formatC(x, format = "f", digits = 4)
}
# Simpan koefisien skala asli
write.csv(
MGWR_ASLI,
file.path(OUT, "43_MGWR_koefisien_skala_asli.csv"),
row.names = FALSE
)
cat("Transformasi koefisien MGWR ke skala asli berhasil.\n")
## Transformasi koefisien MGWR ke skala asli berhasil.
# ============================================================
# BAGIAN KODE 22
# MENAMPILKAN SELURUH 514 PERSAMAAN MGWR SKALA ASLI
# ============================================================
# Memastikan hasil Bagian Kode 20 tersedia
if (!all(c("id", "R2_lokal_evaluatif", "kombinasi") %in%
names(local_table))) {
stop("Objek local_table belum memiliki R-square lokal dan kombinasi.")
}
# Memastikan seluruh koefisien hasil transformasi tersedia
required_coef <- c(
"Intercept_asli",
paste0(xvars, "_coef_asli")
)
if (!all(required_coef %in% names(MGWR_ASLI))) {
stop("Koefisien skala asli belum lengkap.")
}
# Mencocokkan urutan wilayah antara MGWR_ASLI dan local_table
idx_lokal <- match(MGWR_ASLI$id, local_table$id)
if (anyNA(idx_lokal)) {
stop("Pencocokan wilayah antara MGWR_ASLI dan local_table gagal.")
}
# Membentuk tabel persamaan
persamaan_asli_table <- data.frame(
id = MGWR_ASLI$id,
wilayah = MGWR_ASLI$wilayah,
R2_lokal_evaluatif =
local_table$R2_lokal_evaluatif[idx_lokal],
kombinasi =
local_table$kombinasi[idx_lokal],
stringsAsFactors = FALSE
)
# Membentuk persamaan dengan tanda signifikansi BH
persamaan_asli <- character(nrow(MGWR_ASLI))
for (i in seq_len(nrow(MGWR_ASLI))) {
b0 <- MGWR_ASLI$Intercept_asli[i]
terms <- vapply(seq_along(xvars), function(j) {
v <- xvars[j]
# Koefisien pada skala asli
b <- MGWR_ASLI[[paste0(v, "_coef_asli")]][i]
# Status signifikansi dari koreksi BH
sig <- isTRUE(
local_table[[paste0(v, "_sig_BH")]][idx_lokal[i]]
)
paste0(
ifelse(b >= 0, "+", "-"),
fmt_asli(abs(b)),
ifelse(sig, "*", ""),
" X", j
)
}, character(1))
persamaan_asli[i] <- paste0(
"Yhat = ",
fmt_asli(b0),
" ",
paste(terms, collapse = " ")
)
}
persamaan_asli_table$Persamaan_MGWR_skala_asli <-
persamaan_asli
# Mengurutkan seluruh persamaan berdasarkan R-square lokal
persamaan_asli_table <- persamaan_asli_table[
order(
-persamaan_asli_table$R2_lokal_evaluatif,
na.last = TRUE
),
]
rownames(persamaan_asli_table) <- NULL
# Menyimpan seluruh 514 persamaan ke CSV
write.csv(
persamaan_asli_table,
file.path(OUT, "46_seluruh_persamaan_MGWR_skala_asli_urut_R2.csv"),
row.names = FALSE
)
# Memastikan jumlah persamaan
cat(
"\nJumlah persamaan MGWR yang ditampilkan:",
nrow(persamaan_asli_table),
"\n"
)
##
## Jumlah persamaan MGWR yang ditampilkan: 514
# Menampilkan seluruh persamaan secara interaktif di RPubs
DT::datatable(
persamaan_asli_table,
rownames = FALSE,
filter = "top",
extensions = "Buttons",
options = list(
pageLength = 25,
lengthMenu = c(10, 25, 50, 100, 514),
scrollX = TRUE,
autoWidth = TRUE,
dom = "Bfrtip",
buttons = c("copy", "csv", "excel"),
order = list(list(2, "desc"))
),
caption = htmltools::tags$caption(
style = "caption-side: top; text-align: left; font-weight: bold;",
"Seluruh 514 Persamaan Lokal MGWR pada Skala Asli"
)
)