機械学習

演習課題

if (!require(plotly))   install.packages("plotly")
if (!require(quantmod)) install.packages("quantmod")

d <- read.csv(file = "C:/Users/81809/Downloads/機械学習/pcr_tested_daily.csv")
library(DT)
datatable(d)

a <- d$日付
b <- d$PCR.検査実施人数.単日.

plot_ly(x = a, y = b, type = "scatter", mode = "markers+lines") |>
  layout(title = "PCR検査",
         xaxis = list(title = "日付"),
         yaxis = list(title = "人数"))

x <- as.POSIXct(a, format = '%Y/%m/%d')
y <- b

yhat <- rollmean(y, 31, na.pad = T)

plot_ly(type = "scatter", mode = "lines") |>
  add_trace(x = x, y = y,    name = "原系列") |>
  add_trace(x = x, y = yhat, name = "31日移動平均") |>
  config(locale = "ja") |>
  layout(title = "PCR検査実施人数（日別）",
         xaxis = list(title = "年"),
         yaxis = list(title = "実施人数"))

cairo_pdf('corona.pdf')

matplot(x = x, y = y, type = 'l', col = 3, 
        main = 'PCR検査実施人数（日別）', xlab = '年', ylab = '実施人数')
matlines(x = x, y = yhat, col = 1)
grid()
legend('topleft', col = c(3, 1), lty = 1, legend = c('原系列', '31日移動平均'))

dev.off()

## png 
##   2

z <- getSymbols('3092', src  = 'yahooj',
                        from = '2022-01-01',
                        to   = '2022-12-31',
                        auto.assign = F)

# データの保存
write.zoo(z, file = 'zozo.csv', sep = ',', quote = F)

x <- as.POSIXct(index(z), format = '%Y-%m-%d')
y <- z[, 'YJ3092.Close']

# 1日分データをずらすことで当日の日付の株価が１日前のものになる。
ylag1 <- lag(y, k = 1)

# align = 'right'で右寄せ移動平均となる。
yhat5   <- rollmean(ylag1,  5, fill = NA, align = 'right')
yhat25  <- rollmean(ylag1, 25, fill = NA, align = 'right')
yhat25c <- rollmean(y, 25, fill = NA) # 参考（通常の移動平均：中心化移動平均）

matplot(x, y, type = 'l', col = 3,
main = 'ZOZO（3092）', xlab = '日', ylab = '円')
matlines(x, yhat5,   col = 2)
matlines(x, yhat25,  col = 4)
matlines(x, yhat25c, col = 1)
grid()
legend('bottomright', col = c(3, 2, 4, 1), lty = 1,
       legend = c('株価',
                  '5日移動平均',
                  '25日移動平均',
                  '25日中心化移動平均（参考）'))

# （参考）quantmodパッケージのグラフ機能
chartSeries(z, TA = c(addBBands(), addMACD()), type='bar',
            subset='2022-06-01/2022-12-31')

plot_ly(type = "scatter", mode = "lines") |>
  add_trace(x = x, y = paste(y),       name = "株価") |>
  add_trace(x = x, y = paste(yhat5),   name = "5日移動平均") |>
  add_trace(x = x, y = paste(yhat25),  name = "25日移動平均") |>
  add_trace(x = x, y = paste(yhat25c), name = "25日中心化移動平均（参考）") |>
  config(locale = "ja") |> # x軸ラベルの月を日本語表示
  layout(title = "ZOZO（3092）",
         xaxis = list(title = "日"),
         yaxis = list(title = "円"))

# LOESS（平滑化窓幅: span）
x <- seq_along(y)
fit10 <- loess(y ~ x, data = data.frame(x, y), span = 0.1) # 10%
fit30 <- loess(y ~ x, data = data.frame(x, y), span = 0.3) # 30%

matplot(x, y = y, type = "l", col = 3,
main = "ZOZO（3092）", xlab = "日", ylab = "円")
matlines(x, fit10$fitted, col = 1, lwd = 2)
matlines(x, fit30$fitted, col = 2, lwd = 2)
grid()
legend("bottomright", col = c(3, 1, 2), lty = 1,
       legend = c("株価",
                  "LOESS（平滑化窓幅10%）",
                  "LOESS（平滑化窓幅30%）"))

plot_ly(type = "scatter", mode = "lines") |>
  add_trace(x = x, y = paste(y),            name = "株価") |>
  add_trace(x = x, y = paste(fit10$fitted), name = "LOESS（平滑化窓幅10%）") |>
  add_trace(x = x, y = paste(fit30$fitted), name = "LOESS（平滑化窓幅30%）") |>
  layout(title = "ZOZO（3092）", 
         xaxis = list(title = "日"),
         yaxis = list(title = "円"))