Kelompok 7

2023-05-22

Perbandingan FEM Within, LSDV, dan Between Model pada Pendugaan Jumlah Kematian COVID-19 (Jan-Jul 2020)

Pemilihan model FEM tetap berdasarkan Uji Chow dan Uji Hausman

Anggota:

  1. Aprilia Permata Putri (G1401201002)
  2. Dhiya Ulayya Tsabitah (G1401201013)
  3. Muhammad Nachnoer Novatron Fitra Arss (G1401201014)
  4. Fikri Omar Hidayat (G1401201019)
  5. Indri Ramdani (G1401201036)
  6. Angelika Anggreni Batubara (G1401201040)

Package

lapply(c("readxl","plm","lmtest","dplyr","tseries","caret","broom","lmerTest","kableExtra","kSamples","hrbrthemes","ggcorrplot"),library,character.only=T)[[1]]
## [1] "readxl"    "stats"     "graphics"  "grDevices" "utils"     "datasets" 
## [7] "methods"   "base"

Data

data<-read_excel("D:/Users/Documents/ADP/full_grouped.xlsx")
kable(head(data,20),caption="Data")
Data
Date Country Confirmed Deaths Recovered New.cases WHO.Region
2020-01-22 Afghanistan 0 0 0 0 Eastern Mediterranean
2020-01-22 Albania 0 0 0 0 Europe
2020-01-22 Algeria 0 0 0 0 Africa
2020-01-22 Andorra 0 0 0 0 Europe
2020-01-22 Angola 0 0 0 0 Africa
2020-01-22 Antigua and Barbuda 0 0 0 0 Americas
2020-01-22 Argentina 0 0 0 0 Americas
2020-01-22 Armenia 0 0 0 0 Europe
2020-01-22 Australia 0 0 0 0 Western Pacific
2020-01-22 Austria 0 0 0 0 Europe
2020-01-22 Azerbaijan 0 0 0 0 Europe
2020-01-22 Bahamas 0 0 0 0 Americas
2020-01-22 Bahrain 0 0 0 0 Eastern Mediterranean
2020-01-22 Bangladesh 0 0 0 0 South-East Asia
2020-01-22 Barbados 0 0 0 0 Americas
2020-01-22 Belarus 0 0 0 0 Europe
2020-01-22 Belgium 0 0 0 0 Europe
2020-01-22 Belize 0 0 0 0 Americas
2020-01-22 Benin 0 0 0 0 Africa
2020-01-22 Bhutan 0 0 0 0 South-East Asia 
range(data$Date)
## [1] "2020-01-22 UTC" "2020-07-27 UTC"

Eksplorasi

Corrplot

ggcorrplot(cor(data[,c(4,3,5,6)]),colors=c("red","white","navyblue"),
           lab=T,lab_col="white",type="lower")

Linechart

area<-data.frame(Date=data$Date,Value=c(data$Confirmed,
                                        data$Recovered,data$New.cases,
                                        data$Deaths),
                 Var=c(rep("Confirmed",nrow(data)),rep("Recovered",nrow(data)),
                       rep("New cases",nrow(data)),rep("Deaths",nrow(data))),
                 Region=data$WHO.Region)
ggplot(area,aes(x=Date,y=Value/1000,color=Var))+geom_smooth(alpha=0.44,size=1.4,se=F)+
  scale_color_brewer(palette="PuOr")+
  theme_ipsum_rc(grid=F,axis_title_just = "center", axis_text_size = 12,
                  axis_title_size =13)+labs(x="\nDate",
                                            y="Jumlah (ribu jiwa)\n",
                                            col="Status")+facet_wrap(~Region)

Common Effect Model WLS

w<-1/data$Recovered
w<-ifelse(w==Inf,mean(w[which(w!=Inf)]),w)
wls<-lm(Deaths~Confirmed+Recovered+New.cases,
        data=data,weights=w,
        index=c("WHO.Region","Date"));summary(wls)
## Warning: In lm.wfit(x, y, w, offset = offset, singular.ok = singular.ok, 
##     ...) :
##  extra argument 'index' will be disregarded
## 
## Call:
## lm(formula = Deaths ~ Confirmed + Recovered + New.cases, data = data, 
##     weights = w, index = c("WHO.Region", "Date"))
## 
## Weighted Residuals:
##     Min      1Q  Median      3Q     Max 
## -390.44   -1.61    0.73    0.94  537.54 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -3.547144   0.712016  -4.982 6.33e-07 ***
## Confirmed    0.087075   0.000136 640.105  < 2e-16 ***
## Recovered   -0.060971   0.001796 -33.949  < 2e-16 ***
## New.cases   -0.298977   0.006635 -45.062  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 34.97 on 35152 degrees of freedom
## Multiple R-squared:  0.9361, Adjusted R-squared:  0.9361 
## F-statistic: 1.716e+05 on 3 and 35152 DF,  p-value: < 2.2e-16

Fixed Effect Within Model

fe<-plm(Deaths~Confirmed+Recovered+New.cases,data=data,model="within",
        index=c("WHO.Region","Date"));summary(fe)
## Oneway (individual) effect Within Model
## 
## Call:
## plm(formula = Deaths ~ Confirmed + Recovered + New.cases, data = data, 
##     model = "within", index = c("WHO.Region", "Date"))
## 
## Balanced Panel: n = 6, T = 188, N = 35156
## 
## Residuals:
##       Min.    1st Qu.     Median    3rd Qu.       Max. 
## -66799.772   -768.456    -64.485     31.606  29853.518 
## 
## Coefficients:
##              Estimate  Std. Error t-value  Pr(>|t|)    
## Confirmed  0.06644544  0.00029206 227.503 < 2.2e-16 ***
## Recovered -0.03027987  0.00051674 -58.598 < 2.2e-16 ***
## New.cases -0.54035116  0.01113208 -48.540 < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    1.9035e+12
## Residual Sum of Squares: 2.7343e+11
## R-Squared:      0.85635
## Adj. R-Squared: 0.85632
## F-statistic: 69842.4 on 3 and 35147 DF, p-value: < 2.22e-16

#Fixed Effect LSDV Model Without Intercept

lsdv<-lm(Deaths~Confirmed+Recovered+New.cases+factor(Date)+factor(WHO.Region)-1,
   data=data,na.action = na.omit,
   index=c("WHO.Region","Date"));summary(lsdv)
## Warning: In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
##  extra argument 'index' will be disregarded
## 
## Call:
## lm(formula = Deaths ~ Confirmed + Recovered + New.cases + factor(Date) + 
##     factor(WHO.Region) - 1, data = data, na.action = na.omit, 
##     index = c("WHO.Region", "Date"))
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -66026   -555   -200    202  30052 
## 
## Coefficients:
##                                           Estimate Std. Error t value Pr(>|t|)
## Confirmed                                6.637e-02  2.923e-04 227.066  < 2e-16
## Recovered                               -3.017e-02  5.234e-04 -57.640  < 2e-16
## New.cases                               -5.434e-01  1.118e-02 -48.597  < 2e-16
## factor(Date)2020-01-22                  -2.890e+02  2.054e+02  -1.407  0.15941
## factor(Date)2020-01-23                  -2.888e+02  2.054e+02  -1.406  0.15978
## factor(Date)2020-01-24                  -2.883e+02  2.054e+02  -1.403  0.16049
## factor(Date)2020-01-25                  -2.878e+02  2.054e+02  -1.401  0.16123
## factor(Date)2020-01-26                  -2.874e+02  2.054e+02  -1.399  0.16180
## factor(Date)2020-01-27                  -2.871e+02  2.054e+02  -1.398  0.16212
## factor(Date)2020-01-28                  -2.825e+02  2.054e+02  -1.375  0.16907
## factor(Date)2020-01-29                  -2.887e+02  2.054e+02  -1.405  0.15992
## factor(Date)2020-01-30                  -2.849e+02  2.054e+02  -1.387  0.16545
## factor(Date)2020-01-31                  -2.863e+02  2.054e+02  -1.394  0.16330
## factor(Date)2020-02-01                  -2.856e+02  2.054e+02  -1.391  0.16437
## factor(Date)2020-02-02                  -2.791e+02  2.054e+02  -1.359  0.17428
## factor(Date)2020-02-03                  -2.846e+02  2.054e+02  -1.386  0.16590
## factor(Date)2020-02-04                  -2.830e+02  2.054e+02  -1.378  0.16831
## factor(Date)2020-02-05                  -2.846e+02  2.054e+02  -1.386  0.16580
## factor(Date)2020-02-06                  -2.870e+02  2.054e+02  -1.397  0.16227
## factor(Date)2020-02-07                  -2.867e+02  2.054e+02  -1.396  0.16280
## factor(Date)2020-02-08                  -2.894e+02  2.054e+02  -1.409  0.15883
## factor(Date)2020-02-09                  -2.890e+02  2.054e+02  -1.407  0.15942
## factor(Date)2020-02-10                  -2.906e+02  2.054e+02  -1.415  0.15706
## factor(Date)2020-02-11                  -2.922e+02  2.054e+02  -1.422  0.15490
## factor(Date)2020-02-12                  -2.932e+02  2.054e+02  -1.427  0.15346
## factor(Date)2020-02-13                  -2.623e+02  2.054e+02  -1.277  0.20154
## factor(Date)2020-02-14                  -2.844e+02  2.054e+02  -1.384  0.16623
## factor(Date)2020-02-15                  -2.969e+02  2.054e+02  -1.446  0.14827
## factor(Date)2020-02-16                  -2.968e+02  2.054e+02  -1.445  0.14848
## factor(Date)2020-02-17                  -2.972e+02  2.054e+02  -1.447  0.14791
## factor(Date)2020-02-18                  -2.972e+02  2.054e+02  -1.447  0.14788
## factor(Date)2020-02-19                  -3.005e+02  2.054e+02  -1.463  0.14350
## factor(Date)2020-02-20                  -2.993e+02  2.054e+02  -1.457  0.14504
## factor(Date)2020-02-21                  -2.992e+02  2.054e+02  -1.457  0.14521
## factor(Date)2020-02-22                  -2.948e+02  2.054e+02  -1.435  0.15122
## factor(Date)2020-02-23                  -2.990e+02  2.054e+02  -1.456  0.14552
## factor(Date)2020-02-24                  -2.973e+02  2.054e+02  -1.448  0.14774
## factor(Date)2020-02-25                  -2.959e+02  2.054e+02  -1.441  0.14964
## factor(Date)2020-02-26                  -2.953e+02  2.054e+02  -1.437  0.15059
## factor(Date)2020-02-27                  -2.939e+02  2.054e+02  -1.431  0.15249
## factor(Date)2020-02-28                  -2.935e+02  2.054e+02  -1.429  0.15305
## factor(Date)2020-02-29                  -2.918e+02  2.054e+02  -1.421  0.15543
## factor(Date)2020-03-01                  -2.905e+02  2.054e+02  -1.414  0.15732
## factor(Date)2020-03-02                  -2.914e+02  2.054e+02  -1.419  0.15596
## factor(Date)2020-03-03                  -2.898e+02  2.054e+02  -1.411  0.15833
## factor(Date)2020-03-04                  -2.904e+02  2.054e+02  -1.414  0.15741
## factor(Date)2020-03-05                  -2.890e+02  2.054e+02  -1.407  0.15936
## factor(Date)2020-03-06                  -2.862e+02  2.054e+02  -1.393  0.16355
## factor(Date)2020-03-07                  -2.864e+02  2.054e+02  -1.394  0.16322
## factor(Date)2020-03-08                  -2.864e+02  2.054e+02  -1.394  0.16327
## factor(Date)2020-03-09                  -2.866e+02  2.054e+02  -1.395  0.16288
## factor(Date)2020-03-10                  -2.833e+02  2.054e+02  -1.379  0.16775
## factor(Date)2020-03-11                  -2.762e+02  2.054e+02  -1.345  0.17875
## factor(Date)2020-03-12                  -2.819e+02  2.054e+02  -1.373  0.16987
## factor(Date)2020-03-13                  -2.589e+02  2.054e+02  -1.261  0.20745
## factor(Date)2020-03-14                  -2.698e+02  2.054e+02  -1.314  0.18893
## factor(Date)2020-03-15                  -2.697e+02  2.054e+02  -1.313  0.18916
## factor(Date)2020-03-16                  -2.607e+02  2.054e+02  -1.269  0.20430
## factor(Date)2020-03-17                  -2.582e+02  2.054e+02  -1.257  0.20876
## factor(Date)2020-03-18                  -2.490e+02  2.054e+02  -1.213  0.22533
## factor(Date)2020-03-19                  -2.286e+02  2.054e+02  -1.113  0.26582
## factor(Date)2020-03-20                  -2.259e+02  2.054e+02  -1.100  0.27151
## factor(Date)2020-03-21                  -2.197e+02  2.054e+02  -1.070  0.28485
## factor(Date)2020-03-22                  -2.182e+02  2.054e+02  -1.063  0.28799
## factor(Date)2020-03-23                  -1.974e+02  2.054e+02  -0.961  0.33644
## factor(Date)2020-03-24                  -2.013e+02  2.054e+02  -0.980  0.32705
## factor(Date)2020-03-25                  -1.755e+02  2.054e+02  -0.855  0.39279
## factor(Date)2020-03-26                  -1.452e+02  2.054e+02  -0.707  0.47976
## factor(Date)2020-03-27                  -1.436e+02  2.054e+02  -0.699  0.48446
## factor(Date)2020-03-28                  -1.372e+02  2.054e+02  -0.668  0.50434
## factor(Date)2020-03-29                  -1.617e+02  2.054e+02  -0.787  0.43122
## factor(Date)2020-03-30                  -1.452e+02  2.054e+02  -0.707  0.47980
## factor(Date)2020-03-31                  -1.101e+02  2.054e+02  -0.536  0.59182
## factor(Date)2020-04-01                  -1.056e+02  2.054e+02  -0.514  0.60714
## factor(Date)2020-04-02                  -8.305e+01  2.054e+02  -0.404  0.68603
## factor(Date)2020-04-03                  -7.303e+01  2.054e+02  -0.355  0.72222
## factor(Date)2020-04-04                  -7.494e+01  2.054e+02  -0.365  0.71524
## factor(Date)2020-04-05                  -9.680e+01  2.054e+02  -0.471  0.63748
## factor(Date)2020-04-06                  -8.600e+01  2.054e+02  -0.419  0.67548
## factor(Date)2020-04-07                  -5.513e+01  2.054e+02  -0.268  0.78842
## factor(Date)2020-04-08                  -2.421e+01  2.054e+02  -0.118  0.90618
## factor(Date)2020-04-09                  -1.949e+00  2.054e+02  -0.009  0.99243
## factor(Date)2020-04-10                   1.224e+01  2.054e+02   0.060  0.95249
## factor(Date)2020-04-11                  -9.580e+00  2.054e+02  -0.047  0.96280
## factor(Date)2020-04-12                   4.741e+01  2.054e+02   0.231  0.81748
## factor(Date)2020-04-13                  -2.134e+01  2.054e+02  -0.104  0.91724
## factor(Date)2020-04-14                  -4.334e+00  2.054e+02  -0.021  0.98317
## factor(Date)2020-04-15                   4.890e+01  2.054e+02   0.238  0.81182
## factor(Date)2020-04-16                   1.045e+02  2.054e+02   0.509  0.61082
## factor(Date)2020-04-17                   9.890e+01  2.054e+02   0.481  0.63018
## factor(Date)2020-04-18                   7.105e+01  2.054e+02   0.346  0.72943
## factor(Date)2020-04-19                   9.095e+01  2.054e+02   0.443  0.65793
## factor(Date)2020-04-20                   7.659e+01  2.054e+02   0.373  0.70925
## factor(Date)2020-04-21                   9.922e+01  2.054e+02   0.483  0.62906
## factor(Date)2020-04-22                   1.237e+02  2.054e+02   0.602  0.54712
## factor(Date)2020-04-23                   1.624e+02  2.054e+02   0.791  0.42911
## factor(Date)2020-04-24                   1.984e+02  2.054e+02   0.966  0.33412
## factor(Date)2020-04-25                   1.674e+02  2.054e+02   0.815  0.41499
## factor(Date)2020-04-26                   1.320e+02  2.054e+02   0.642  0.52059
## factor(Date)2020-04-27                   1.244e+02  2.054e+02   0.605  0.54487
## factor(Date)2020-04-28                   1.569e+02  2.054e+02   0.764  0.44500
## factor(Date)2020-04-29                   1.844e+02  2.054e+02   0.898  0.36924
## factor(Date)2020-04-30                   2.089e+02  2.054e+02   1.017  0.30915
## factor(Date)2020-05-01                   2.214e+02  2.054e+02   1.078  0.28105
## factor(Date)2020-05-02                   2.122e+02  2.054e+02   1.033  0.30146
## factor(Date)2020-05-03                   1.959e+02  2.054e+02   0.954  0.34012
## factor(Date)2020-05-04                   1.918e+02  2.054e+02   0.934  0.35041
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## factor(Date)2020-05-06                   2.520e+02  2.054e+02   1.227  0.21986
## factor(Date)2020-05-07                   2.574e+02  2.054e+02   1.253  0.21016
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## factor(Date)2020-05-09                   2.472e+02  2.054e+02   1.204  0.22874
## factor(Date)2020-05-10                   2.166e+02  2.054e+02   1.055  0.29155
## factor(Date)2020-05-11                   2.157e+02  2.054e+02   1.050  0.29361
## factor(Date)2020-05-12                   2.428e+02  2.054e+02   1.182  0.23718
## factor(Date)2020-05-13                   2.533e+02  2.054e+02   1.233  0.21755
## factor(Date)2020-05-14                   2.887e+02  2.054e+02   1.405  0.15991
## factor(Date)2020-05-15                   2.878e+02  2.054e+02   1.401  0.16122
## factor(Date)2020-05-16                   2.825e+02  2.054e+02   1.375  0.16907
## factor(Date)2020-05-17                   2.297e+02  2.054e+02   1.119  0.26331
## factor(Date)2020-05-18                   2.528e+02  2.054e+02   1.231  0.21830
## factor(Date)2020-05-19                   2.768e+02  2.054e+02   1.347  0.17784
## factor(Date)2020-05-20                   2.943e+02  2.054e+02   1.433  0.15192
## factor(Date)2020-05-21                   3.002e+02  2.054e+02   1.461  0.14390
## factor(Date)2020-05-22                   3.092e+02  2.054e+02   1.506  0.13220
## factor(Date)2020-05-23                   2.973e+02  2.054e+02   1.447  0.14783
## factor(Date)2020-05-24                   2.601e+02  2.054e+02   1.266  0.20540
## factor(Date)2020-05-25                   2.225e+02  2.054e+02   1.083  0.27873
## factor(Date)2020-05-26                   2.366e+02  2.054e+02   1.152  0.24930
## factor(Date)2020-05-27                   2.668e+02  2.054e+02   1.299  0.19392
## factor(Date)2020-05-28                   3.089e+02  2.054e+02   1.504  0.13265
## factor(Date)2020-05-29                   3.089e+02  2.054e+02   1.504  0.13258
## factor(Date)2020-05-30                   3.419e+02  2.054e+02   1.665  0.09598
## factor(Date)2020-05-31                   2.434e+02  2.054e+02   1.185  0.23600
## factor(Date)2020-06-01                   1.988e+02  2.054e+02   0.968  0.33305
## factor(Date)2020-06-02                   2.751e+02  2.054e+02   1.339  0.18045
## factor(Date)2020-06-03                   2.688e+02  2.054e+02   1.309  0.19062
## factor(Date)2020-06-04                   2.844e+02  2.054e+02   1.385  0.16614
## factor(Date)2020-06-05                   2.859e+02  2.054e+02   1.392  0.16389
## factor(Date)2020-06-06                   2.847e+02  2.054e+02   1.386  0.16574
## factor(Date)2020-06-07                   1.995e+02  2.054e+02   0.971  0.33148
## factor(Date)2020-06-08                   1.781e+02  2.054e+02   0.867  0.38577
## factor(Date)2020-06-09                   2.378e+02  2.054e+02   1.158  0.24705
## factor(Date)2020-06-10                   2.588e+02  2.054e+02   1.260  0.20775
## factor(Date)2020-06-11                   2.609e+02  2.054e+02   1.270  0.20408
## factor(Date)2020-06-12                   2.245e+02  2.054e+02   1.093  0.27435
## factor(Date)2020-06-13                   2.327e+02  2.054e+02   1.133  0.25716
## factor(Date)2020-06-14                   2.072e+02  2.054e+02   1.009  0.31310
## factor(Date)2020-06-15                   1.558e+02  2.054e+02   0.759  0.44814
## factor(Date)2020-06-16                   2.213e+02  2.054e+02   1.077  0.28129
## factor(Date)2020-06-17                   2.193e+02  2.054e+02   1.068  0.28566
## factor(Date)2020-06-18                   2.040e+02  2.054e+02   0.993  0.32074
## factor(Date)2020-06-19                   3.078e+02  2.054e+02   1.498  0.13402
## factor(Date)2020-06-20                   2.252e+02  2.054e+02   1.096  0.27293
## factor(Date)2020-06-21                   1.275e+02  2.054e+02   0.621  0.53491
## factor(Date)2020-06-22                   1.394e+02  2.054e+02   0.679  0.49727
## factor(Date)2020-06-23                   2.057e+02  2.054e+02   1.002  0.31656
## factor(Date)2020-06-24                   2.087e+02  2.054e+02   1.016  0.30963
## factor(Date)2020-06-25                   2.154e+02  2.054e+02   1.049  0.29436
## factor(Date)2020-06-26                   2.296e+02  2.054e+02   1.118  0.26376
## factor(Date)2020-06-27                   1.690e+02  2.054e+02   0.823  0.41071
## factor(Date)2020-06-28                   9.667e+01  2.054e+02   0.471  0.63796
## factor(Date)2020-06-29                   6.446e+01  2.054e+02   0.314  0.75369
## factor(Date)2020-06-30                   9.360e+01  2.054e+02   0.456  0.64868
## factor(Date)2020-07-01                   1.890e+02  2.054e+02   0.920  0.35746
## factor(Date)2020-07-02                   1.596e+02  2.054e+02   0.777  0.43732
## factor(Date)2020-07-03                   1.195e+02  2.054e+02   0.582  0.56083
## factor(Date)2020-07-04                   7.684e+01  2.055e+02   0.374  0.70843
## factor(Date)2020-07-05                   1.805e+01  2.055e+02   0.088  0.93000
## factor(Date)2020-07-06                  -4.577e+01  2.055e+02  -0.223  0.82373
## factor(Date)2020-07-07                   6.183e+01  2.055e+02   0.301  0.76350
## factor(Date)2020-07-08                   4.329e+01  2.055e+02   0.211  0.83313
## factor(Date)2020-07-09                   6.087e+01  2.055e+02   0.296  0.76707
## factor(Date)2020-07-10                   4.179e+01  2.055e+02   0.203  0.83883
## factor(Date)2020-07-11                  -3.578e+01  2.055e+02  -0.174  0.86180
## factor(Date)2020-07-12                  -1.338e+02  2.055e+02  -0.651  0.51507
## factor(Date)2020-07-13                  -1.589e+02  2.055e+02  -0.773  0.43945
## factor(Date)2020-07-14                  -1.010e+02  2.055e+02  -0.492  0.62301
## factor(Date)2020-07-15                  -9.986e+01  2.055e+02  -0.486  0.62706
## factor(Date)2020-07-16                  -7.171e+01  2.055e+02  -0.349  0.72715
## factor(Date)2020-07-17                  -1.264e+02  2.055e+02  -0.615  0.53874
## factor(Date)2020-07-18                  -1.691e+02  2.056e+02  -0.822  0.41080
## factor(Date)2020-07-19                  -2.764e+02  2.056e+02  -1.344  0.17885
## factor(Date)2020-07-20                  -3.248e+02  2.056e+02  -1.580  0.11418
## factor(Date)2020-07-21                  -2.683e+02  2.056e+02  -1.305  0.19183
## factor(Date)2020-07-22                  -1.653e+02  2.056e+02  -0.804  0.42127
## factor(Date)2020-07-23                  -1.789e+02  2.056e+02  -0.870  0.38426
## factor(Date)2020-07-24                  -2.135e+02  2.056e+02  -1.039  0.29901
## factor(Date)2020-07-25                  -3.173e+02  2.056e+02  -1.543  0.12282
## factor(Date)2020-07-26                  -4.943e+02  2.057e+02  -2.403  0.01628
## factor(Date)2020-07-27                  -4.483e+02  2.057e+02  -2.180  0.02930
## factor(WHO.Region)Americas               3.658e+02  4.564e+01   8.016 1.13e-15
## factor(WHO.Region)Eastern Mediterranean -1.467e+02  5.241e+01  -2.798  0.00514
## factor(WHO.Region)Europe                 8.163e+02  4.010e+01  20.358  < 2e-16
## factor(WHO.Region)South-East Asia       -1.272e+02  7.090e+01  -1.795  0.07271
## factor(WHO.Region)Western Pacific        4.910e-01  5.871e+01   0.008  0.99333
##                                            
## Confirmed                               ***
## Recovered                               ***
## New.cases                               ***
## factor(Date)2020-01-22                     
## factor(Date)2020-01-23                     
## factor(Date)2020-01-24                     
## factor(Date)2020-01-25                     
## factor(Date)2020-01-26                     
## factor(Date)2020-01-27                     
## factor(Date)2020-01-28                     
## factor(Date)2020-01-29                     
## factor(Date)2020-01-30                     
## factor(Date)2020-01-31                     
## factor(Date)2020-02-01                     
## factor(Date)2020-02-02                     
## factor(Date)2020-02-03                     
## factor(Date)2020-02-04                     
## factor(Date)2020-02-05                     
## factor(Date)2020-02-06                     
## factor(Date)2020-02-07                     
## factor(Date)2020-02-08                     
## factor(Date)2020-02-09                     
## factor(Date)2020-02-10                     
## factor(Date)2020-02-11                     
## factor(Date)2020-02-12                     
## factor(Date)2020-02-13                     
## factor(Date)2020-02-14                     
## factor(Date)2020-02-15                     
## factor(Date)2020-02-16                     
## factor(Date)2020-02-17                     
## factor(Date)2020-02-18                     
## factor(Date)2020-02-19                     
## factor(Date)2020-02-20                     
## factor(Date)2020-02-21                     
## factor(Date)2020-02-22                     
## factor(Date)2020-02-23                     
## factor(Date)2020-02-24                     
## factor(Date)2020-02-25                     
## factor(Date)2020-02-26                     
## factor(Date)2020-02-27                     
## factor(Date)2020-02-28                     
## factor(Date)2020-02-29                     
## factor(Date)2020-03-01                     
## factor(Date)2020-03-02                     
## factor(Date)2020-03-03                     
## factor(Date)2020-03-04                     
## factor(Date)2020-03-05                     
## factor(Date)2020-03-06                     
## factor(Date)2020-03-07                     
## factor(Date)2020-03-08                     
## factor(Date)2020-03-09                     
## factor(Date)2020-03-10                     
## factor(Date)2020-03-11                     
## factor(Date)2020-03-12                     
## factor(Date)2020-03-13                     
## factor(Date)2020-03-14                     
## factor(Date)2020-03-15                     
## factor(Date)2020-03-16                     
## factor(Date)2020-03-17                     
## factor(Date)2020-03-18                     
## factor(Date)2020-03-19                     
## factor(Date)2020-03-20                     
## factor(Date)2020-03-21                     
## factor(Date)2020-03-22                     
## factor(Date)2020-03-23                     
## factor(Date)2020-03-24                     
## factor(Date)2020-03-25                     
## factor(Date)2020-03-26                     
## factor(Date)2020-03-27                     
## factor(Date)2020-03-28                     
## factor(Date)2020-03-29                     
## factor(Date)2020-03-30                     
## factor(Date)2020-03-31                     
## factor(Date)2020-04-01                     
## factor(Date)2020-04-02                     
## factor(Date)2020-04-03                     
## factor(Date)2020-04-04                     
## factor(Date)2020-04-05                     
## factor(Date)2020-04-06                     
## factor(Date)2020-04-07                     
## factor(Date)2020-04-08                     
## factor(Date)2020-04-09                     
## factor(Date)2020-04-10                     
## factor(Date)2020-04-11                     
## factor(Date)2020-04-12                     
## factor(Date)2020-04-13                     
## factor(Date)2020-04-14                     
## factor(Date)2020-04-15                     
## factor(Date)2020-04-16                     
## factor(Date)2020-04-17                     
## factor(Date)2020-04-18                     
## factor(Date)2020-04-19                     
## factor(Date)2020-04-20                     
## factor(Date)2020-04-21                     
## factor(Date)2020-04-22                     
## factor(Date)2020-04-23                     
## factor(Date)2020-04-24                     
## factor(Date)2020-04-25                     
## factor(Date)2020-04-26                     
## factor(Date)2020-04-27                     
## factor(Date)2020-04-28                     
## factor(Date)2020-04-29                     
## factor(Date)2020-04-30                     
## factor(Date)2020-05-01                     
## factor(Date)2020-05-02                     
## factor(Date)2020-05-03                     
## factor(Date)2020-05-04                     
## factor(Date)2020-05-05                     
## factor(Date)2020-05-06                     
## factor(Date)2020-05-07                     
## factor(Date)2020-05-08                     
## factor(Date)2020-05-09                     
## factor(Date)2020-05-10                     
## factor(Date)2020-05-11                     
## factor(Date)2020-05-12                     
## factor(Date)2020-05-13                     
## factor(Date)2020-05-14                     
## factor(Date)2020-05-15                     
## factor(Date)2020-05-16                     
## factor(Date)2020-05-17                     
## factor(Date)2020-05-18                     
## factor(Date)2020-05-19                     
## factor(Date)2020-05-20                     
## factor(Date)2020-05-21                     
## factor(Date)2020-05-22                     
## factor(Date)2020-05-23                     
## factor(Date)2020-05-24                     
## factor(Date)2020-05-25                     
## factor(Date)2020-05-26                     
## factor(Date)2020-05-27                     
## factor(Date)2020-05-28                     
## factor(Date)2020-05-29                     
## factor(Date)2020-05-30                  .  
## factor(Date)2020-05-31                     
## factor(Date)2020-06-01                     
## factor(Date)2020-06-02                     
## factor(Date)2020-06-03                     
## factor(Date)2020-06-04                     
## factor(Date)2020-06-05                     
## factor(Date)2020-06-06                     
## factor(Date)2020-06-07                     
## factor(Date)2020-06-08                     
## factor(Date)2020-06-09                     
## factor(Date)2020-06-10                     
## factor(Date)2020-06-11                     
## factor(Date)2020-06-12                     
## factor(Date)2020-06-13                     
## factor(Date)2020-06-14                     
## factor(Date)2020-06-15                     
## factor(Date)2020-06-16                     
## factor(Date)2020-06-17                     
## factor(Date)2020-06-18                     
## factor(Date)2020-06-19                     
## factor(Date)2020-06-20                     
## factor(Date)2020-06-21                     
## factor(Date)2020-06-22                     
## factor(Date)2020-06-23                     
## factor(Date)2020-06-24                     
## factor(Date)2020-06-25                     
## factor(Date)2020-06-26                     
## factor(Date)2020-06-27                     
## factor(Date)2020-06-28                     
## factor(Date)2020-06-29                     
## factor(Date)2020-06-30                     
## factor(Date)2020-07-01                     
## factor(Date)2020-07-02                     
## factor(Date)2020-07-03                     
## factor(Date)2020-07-04                     
## factor(Date)2020-07-05                     
## factor(Date)2020-07-06                     
## factor(Date)2020-07-07                     
## factor(Date)2020-07-08                     
## factor(Date)2020-07-09                     
## factor(Date)2020-07-10                     
## factor(Date)2020-07-11                     
## factor(Date)2020-07-12                     
## factor(Date)2020-07-13                     
## factor(Date)2020-07-14                     
## factor(Date)2020-07-15                     
## factor(Date)2020-07-16                     
## factor(Date)2020-07-17                     
## factor(Date)2020-07-18                     
## factor(Date)2020-07-19                     
## factor(Date)2020-07-20                     
## factor(Date)2020-07-21                     
## factor(Date)2020-07-22                     
## factor(Date)2020-07-23                     
## factor(Date)2020-07-24                     
## factor(Date)2020-07-25                     
## factor(Date)2020-07-26                  *  
## factor(Date)2020-07-27                  *  
## factor(WHO.Region)Americas              ***
## factor(WHO.Region)Eastern Mediterranean ** 
## factor(WHO.Region)Europe                ***
## factor(WHO.Region)South-East Asia       .  
## factor(WHO.Region)Western Pacific          
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2787 on 34960 degrees of freedom
## Multiple R-squared:  0.8641, Adjusted R-squared:  0.8633 
## F-statistic:  1134 on 196 and 34960 DF,  p-value: < 2.2e-16

Uji Chow

pFtest(fe,wls)#bagusan fe
## 
##  F test for individual effects
## 
## data:  Deaths ~ Confirmed + Recovered + New.cases
## F = 4370.4, df1 = 5, df2 = 35147, p-value < 2.2e-16
## alternative hypothesis: significant effects

Uji Efek Individu dan waktu

plmtest(fe,type="bp",effect="individual") #terdapat pengaruh individu sekaligus waktu
## 
##  Lagrange Multiplier Test - (Breusch-Pagan)
## 
## data:  Deaths ~ Confirmed + Recovered + New.cases
## chisq = 52346, df = 1, p-value < 2.2e-16
## alternative hypothesis: significant effects

Uji Efek Individu

plmtest(fe,type="bp",effect="individual") #terdapat pengaruh individu
## 
##  Lagrange Multiplier Test - (Breusch-Pagan)
## 
## data:  Deaths ~ Confirmed + Recovered + New.cases
## chisq = 52346, df = 1, p-value < 2.2e-16
## alternative hypothesis: significant effects

Uji Efek Waktu

plmtest(fe,type="bp",effect="time") #terdapat pengaruh waktu
## 
##  Lagrange Multiplier Test - time effects (Breusch-Pagan)
## 
## data:  Deaths ~ Confirmed + Recovered + New.cases
## chisq = 4.9723, df = 1, p-value = 0.02576
## alternative hypothesis: significant effects
#Maka yang digunakan efek twoways Fixed Effect Within Model

Model Fixed Effect Final (Efek Dua Arah)

fetw<-plm(Deaths~Confirmed+Recovered+New.cases,data=data,model="within",
        index=c("WHO.Region","Date"),effect="twoways");summary(fe)
## Oneway (individual) effect Within Model
## 
## Call:
## plm(formula = Deaths ~ Confirmed + Recovered + New.cases, data = data, 
##     model = "within", index = c("WHO.Region", "Date"))
## 
## Balanced Panel: n = 6, T = 188, N = 35156
## 
## Residuals:
##       Min.    1st Qu.     Median    3rd Qu.       Max. 
## -66799.772   -768.456    -64.485     31.606  29853.518 
## 
## Coefficients:
##              Estimate  Std. Error t-value  Pr(>|t|)    
## Confirmed  0.06644544  0.00029206 227.503 < 2.2e-16 ***
## Recovered -0.03027987  0.00051674 -58.598 < 2.2e-16 ***
## New.cases -0.54035116  0.01113208 -48.540 < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    1.9035e+12
## Residual Sum of Squares: 2.7343e+11
## R-Squared:      0.85635
## Adj. R-Squared: 0.85632
## F-statistic: 69842.4 on 3 and 35147 DF, p-value: < 2.22e-16

REM Individu

re<-plm(Deaths~Confirmed+Recovered+New.cases,data=data,model="random",
        index=c("WHO.Region","Date"));summary(re)
## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
##  to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")
## Oneway (individual) effect Random Effect Model 
##    (Swamy-Arora's transformation)
## 
## Call:
## plm(formula = Deaths ~ Confirmed + Recovered + New.cases, data = data, 
##     model = "random", index = c("WHO.Region", "Date"))
## 
## Balanced Panel: n = 6, T = 188, N = 35156
## 
## Effects:
##                   var std.dev share
## idiosyncratic 7779658    2789 0.671
## individual    3810653    1952 0.329
## theta: 0.8964
## 
## Residuals:
##        Min.     1st Qu.      Median     3rd Qu.        Max. 
## -66800.8876   -714.3100    -85.0118      1.9869  29860.7354 
## 
## Coefficients:
##                Estimate  Std. Error  z-value Pr(>|z|)    
## (Intercept)  2.5631e+02  1.4355e+02   1.7855  0.07418 .  
## Confirmed    6.6450e-02  2.9206e-04 227.5172  < 2e-16 ***
## Recovered   -3.0280e-02  5.1675e-04 -58.5972  < 2e-16 ***
## New.cases   -5.4051e-01  1.1132e-02 -48.5568  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    1.9039e+12
## Residual Sum of Squares: 2.7349e+11
## R-Squared:      0.85636
## Adj. R-Squared: 0.85634
## Chisq: 209565 on 3 DF, p-value: < 2.22e-16

Uji Efek Individu

plmtest(re,type="bp",effect="individual")
## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
##  to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")
## 
##  Lagrange Multiplier Test - (Breusch-Pagan)
## 
## data:  Deaths ~ Confirmed + Recovered + New.cases
## chisq = 52346, df = 1, p-value < 2.2e-16
## alternative hypothesis: significant effects

Uji Efek Waktu

plmtest(re,type="bp",effect="time")
## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
##  to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")
## 
##  Lagrange Multiplier Test - time effects (Breusch-Pagan)
## 
## data:  Deaths ~ Confirmed + Recovered + New.cases
## chisq = 4.9723, df = 1, p-value = 0.02576
## alternative hypothesis: significant effects

Uji Efek Twoways

plmtest(re,type="bp",effect="twoways") #Maka efek twoways yang akan digunakan
## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
##  to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")
## 
##  Lagrange Multiplier Test - two-ways effects (Breusch-Pagan)
## 
## data:  Deaths ~ Confirmed + Recovered + New.cases
## chisq = 52351, df = 2, p-value < 2.2e-16
## alternative hypothesis: significant effects

REM Final (twoways)

re<-plm(Deaths~Confirmed+Recovered+New.cases,data=data,model="random",
        index=c("WHO.Region","Date"),effect="twoways");summary(re)
## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
##  to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")
## Twoways effects Random Effect Model 
##    (Swamy-Arora's transformation)
## 
## Call:
## plm(formula = Deaths ~ Confirmed + Recovered + New.cases, data = data, 
##     effect = "twoways", model = "random", index = c("WHO.Region", 
##         "Date"))
## 
## Balanced Panel: n = 6, T = 188, N = 35156
## 
## Effects:
##                   var std.dev share
## idiosyncratic 7768419    2787 0.671
## individual    3810712    1952 0.329
## time                0       0 0.000
## theta: 0.8964 (id) 0 (time) 0 (total)
## 
## Residuals:
##        Min.     1st Qu.      Median     3rd Qu.        Max. 
## -66800.8805   -714.3496    -84.9904      2.0083  29860.7304 
## 
## Coefficients:
##                Estimate  Std. Error  z-value Pr(>|z|)    
## (Intercept)  2.5631e+02  1.4366e+02   1.7842  0.07439 .  
## Confirmed    6.6450e-02  2.9206e-04 227.5173  < 2e-16 ***
## Recovered   -3.0280e-02  5.1675e-04 -58.5972  < 2e-16 ***
## New.cases   -5.4051e-01  1.1132e-02 -48.5568  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    1.9039e+12
## Residual Sum of Squares: 2.7349e+11
## R-Squared:      0.85636
## Adj. R-Squared: 0.85634
## Chisq: 209565 on 3 DF, p-value: < 2.22e-16

Hausman Test

kable(tidy(phtest(fetw,re)),digits=3,caption="Hausman Test") #tetap bagusan FE twoways
Hausman Test
statistic p.value parameter method alternative
530.259 0 3 Hausman Test one model is inconsistent

Berdasarkan uji Hausman, model yang terbaik adalah FEM twoways. Dan dari hasil sebelumnya, performa model FEM LSDV sedikit lebih baik dibandingkan FEM Within, maka model sementara yang dipilih adalah FEM LSDV twoways (menyertakan dummy individu dan waktu)

Between Model

Between Model Time: Efek waktu yang dimasukkan adalah rataan efek individu pada tiap periode waktu

Between Model Individu: Efek waktu yang dimasukkan adalah rataan efek waktu pada tiap individu

Eksplorasi Rataan Peubah Tiap Periode Waktu

ggplot(area,aes(x=Date,y=Value/1000,color=Var))+geom_smooth(alpha=0.44,size=1.4,se=F)+
  scale_color_brewer(palette="PuOr")+
  theme_ipsum_rc(grid=F,axis_title_just = "center", axis_text_size = 12,
                  axis_title_size =13)+labs(x="\nDate",
                                            y="Rataan (ribu jiwa)\n",
                                            col="Status")

Eksplorasi Rataan Peubah Tiap Region

ar<-area%>%group_by(Region,Var)%>%summarise(mean=mean(Value/1000))
ggplot(ar,aes(x=reorder(Region,mean),y=mean,fill=Var))+geom_bar(stat="identity")+
  scale_fill_brewer(palette = "PuOr")+
  theme_ipsum_rc(grid=F,axis_title_just = "center",
                 axis_title_size = 12)+labs(x="\nRegion",
                                            y="Rataan (ribu jiwa)\n")+coord_polar("y")

Between Time

bt<-plm(Deaths~Confirmed+Recovered+New.cases,data=data,model="between",
        index=c("WHO.Region","Date"),effect="time");summary(bt)
## Oneway (time) effect Between Model
## 
## Call:
## plm(formula = Deaths ~ Confirmed + Recovered + New.cases, data = data, 
##     effect = "time", model = "between", index = c("WHO.Region", 
##         "Date"))
## 
## Balanced Panel: n = 6, T = 188, N = 35156
## Observations used in estimation: 188
## 
## Residuals:
##      Min.   1st Qu.    Median   3rd Qu.      Max. 
## -200.8678  -28.5507    5.8869   21.8934  136.3596 
## 
## Coefficients:
##                Estimate  Std. Error  t-value  Pr(>|t|)    
## (Intercept) -20.0610785   6.6109058  -3.0345  0.002758 ** 
## Confirmed     0.1244437   0.0014463  86.0427 < 2.2e-16 ***
## Recovered    -0.1341790   0.0020540 -65.3269 < 2.2e-16 ***
## New.cases    -0.4179313   0.0364848 -11.4550 < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    253970000
## Residual Sum of Squares: 470720
## R-Squared:      0.99815
## Adj. R-Squared: 0.99812
## F-statistic: 33030.6 on 3 and 184 DF, p-value: < 2.22e-16

Between Individu

bi<-plm(Deaths~Confirmed+Recovered+New.cases,data=data,model="between",
        index=c("WHO.Region","Date"),effect="individual");summary(bi)
## Oneway (individual) effect Between Model
## 
## Call:
## plm(formula = Deaths ~ Confirmed + Recovered + New.cases, data = data, 
##     effect = "individual", model = "between", index = c("WHO.Region", 
##         "Date"))
## 
## Balanced Panel: n = 6, T = 188, N = 35156
## Observations used in estimation: 6
## 
## Residuals:
##                Africa              Americas Eastern Mediterranean 
##                6.8453             -125.4668             -263.5718 
##                Europe       South-East Asia       Western Pacific 
##              382.7503              162.1161             -162.6732 
## 
## Coefficients:
##               Estimate Std. Error t-value Pr(>|t|)  
## (Intercept) -13.836330 385.623666 -0.0359  0.97464  
## Confirmed     0.111137   0.035129  3.1637  0.08706 .
## Recovered    -0.048357   0.093253 -0.5186  0.65574  
## New.cases    -1.903861   1.007163 -1.8903  0.19928  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    6155900
## Residual Sum of Squares: 284500
## R-Squared:      0.95378
## Adj. R-Squared: 0.88446
## F-statistic: 13.7583 on 3 and 2 DF, p-value: 0.068517

Dapat dilihat bahwa Between Model memiliki performa yang jauh lebih baik dibandingkan dengan model FEM within ataupun FEM LSDV. Namun, tidak ada peubah yang signifikan pada Between Individu, meskipun memiliki R-square 0.95, tetapi nilai adjusted R-square nya lebih rendah yaitu 0,88 sedangkan pada Between Time semua peubah signifikan dan baik R-square maupun adjusted R-Square memiliki nilai yang tidak begitu timpang, artinya tidak terjadi pergeseran yang berarti pada performa model ketika terjadi penambahan peubah untuk Between Model dengan efek waktu.

Pengecekan & Uji Asumsi FEM Between (Time)

hist(bt$residuals,freq = F,col="steelblue")
lines(density(bt$residuals),col="coral",lwd=3)

set.seed(123);ad.test(bt$residuals, rnorm(length(bt$residuals), mean=mean(bt$residuals), sd=sd(bt$residuals)))#normal
## 
## 
##  Anderson-Darling k-sample test.
## 
## Number of samples:  2
## Sample sizes:  188, 188
## Number of ties: 0
## 
## Mean of  Anderson-Darling  Criterion: 1
## Standard deviation of  Anderson-Darling  Criterion: 0.75753
## 
## T.AD = ( Anderson-Darling  Criterion - mean)/sigma
## 
## Null Hypothesis: All samples come from a common population.
## 
##               AD   T.AD  asympt. P-value
## version 1: 1.465 0.6138           0.1844
## version 2: 1.470 0.6147           0.1844
qqnorm(bt$residuals,col="steelblue")
qqline(rnorm(length(bt$residuals),mean(bt$residuals),sd(bt$residuals)),
       col="coral",lwd=3)

kable(tidy(bgtest(bt)),digits=3, caption="Breusch-Godfrey Test")#tidak ada autokol
Breusch-Godfrey Test
statistic p.value parameter method
2.957 0.085 1 Breusch-Godfrey test for serial correlation of order up to 1 
kable(tidy(gqtest(bt)),sigits=3,caption="Goldfeld Quandt Test")#ragam heterogen
Goldfeld Quandt Test
df1 df2 statistic p.value method alternative
17574 17574 1.792534 0 Goldfeld-Quandt test variance increases from segment 1 to 2

Sisaan secara eksploratif cenderung menjulur ke kiri, meskipun cukup bukti dikatakan menyebar normal pada Uji Anderson, tidak ada autokol, tetapi ragam heterogen

Model Final Between Model (time)

Pemodelan dengan transformasi logaritma natural untuk peubah X, dan transformasi kuadratik untuk peubah Y, karena sebaran sisaan secara eksploratif cenderung menjulur ke kiri. Transformasi X dan Y digunakan untuk menangani keadaan ketidaknormalan sisaan sekaligus kondisi linearitas dan heteroskedastisitas

btnew<-plm(Deaths^2~log(Confirmed-min(Confirmed)+1)+log(Recovered-min(Recovered)+1)+log(New.cases-min(Recovered)+1),data=data,model="between", index=c("WHO.Region","Date"),effect="time");summary(btnew)
## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
##  to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")
## Oneway (time) effect Between Model
## 
## Call:
## plm(formula = Deaths^2 ~ log(Confirmed - min(Confirmed) + 1) + 
##     log(Recovered - min(Recovered) + 1) + log(New.cases - min(Recovered) + 
##     1), data = data, effect = "time", model = "between", index = c("WHO.Region", 
##     "Date"))
## 
## Balanced Panel: n = 6, T = 188, N = 35156
## Observations used in estimation: 188
## 
## Residuals:
##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
## -50190341 -14039225  -4125714         0   9945573  78219811 
## 
## Coefficients:
##                                      Estimate Std. Error  t-value  Pr(>|t|)    
## (Intercept)                          13617307    3791755   3.5913 0.0004221 ***
## log(Confirmed - min(Confirmed) + 1) -98581841    9842519 -10.0159 < 2.2e-16 ***
## log(Recovered - min(Recovered) + 1)  74823824    4641561  16.1204 < 2.2e-16 ***
## log(New.cases - min(Recovered) + 1) 106755480   13737075   7.7713 5.304e-13 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    7.7831e+17
## Residual Sum of Squares: 8.8953e+16
## R-Squared:      0.88571
## Adj. R-Squared: 0.88385
## F-statistic: 475.313 on 3 and 184 DF, p-value: < 2.22e-16

Pengecekan Asumsi

hist(btnew$residuals,freq = F,col="steelblue")
lines(density(btnew$residuals),col="coral",lwd=3)

set.seed(123);ad.test(btnew$residuals, rnorm(length(btnew$residuals), mean=mean(btnew$residuals), sd=sd(btnew$residuals)))#normal
## 
## 
##  Anderson-Darling k-sample test.
## 
## Number of samples:  2
## Sample sizes:  188, 188
## Number of ties: 0
## 
## Mean of  Anderson-Darling  Criterion: 1
## Standard deviation of  Anderson-Darling  Criterion: 0.75753
## 
## T.AD = ( Anderson-Darling  Criterion - mean)/sigma
## 
## Null Hypothesis: All samples come from a common population.
## 
##                AD    T.AD  asympt. P-value
## version 1: 0.5715 -0.5657           0.6765
## version 2: 0.5690 -0.5688           0.6786
qqnorm(btnew$residuals,col="steelblue")
qqline(rnorm(length(btnew$residuals),mean(btnew$residuals),sd(btnew$residuals)),
       col="coral",lwd=3)

kable(tidy(bgtest(btnew)),digits=3, caption="Breusch-Godfrey Test")#tidak ada autokol
Breusch-Godfrey Test
statistic p.value parameter method
1.849 0.174 1 Breusch-Godfrey test for serial correlation of order up to 1 
kable(tidy(gqtest(btnew)),sigits=3,caption="Goldfeld Quandt Test")#ragam homogen
## Multiple parameters; naming those columns df1, df2
Goldfeld Quandt Test
df1 df2 statistic p.value method alternative
17574 17574 0.0272419 1 Goldfeld-Quandt test variance increases from segment 1 to 2

Semua asumsi sisaan terpenuhi