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summary(cars)
## speed dist
## Min. : 4.0 Min. : 2.00
## 1st Qu.:12.0 1st Qu.: 26.00
## Median :15.0 Median : 36.00
## Mean :15.4 Mean : 42.98
## 3rd Qu.:19.0 3rd Qu.: 56.00
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px <- seq(as.POSIXct('2023-01-01 01:00:00'),
as.POSIXct('2023-01-01 12:00:00'), by = 60 * 60)
n <- length(px)
# ホワイトノイズ
set.seed(5963)
x <- rnorm(n, mean = 0, sd = 1)
# 時系列を扱うts型オブジェクトを作成
y <- ts(x) # 原系列
x <- 1:n
# 時系列を扱うts型オブジェクトを作成
y <- ts(x) # 原系列
y.lag1 <- lag(y, k = -1) # 1次ラグ系列
y.lag2 <- lag(y, k = -2) # 2次ラグ系列
y.lag3 <- lag(y, k = -3) # 3次ラグ系列
ts4 <- cbind(y, y.lag1, y.lag2, y.lag3)[1:n, ]
d <- as.data.frame(ts4)
d
## y y.lag1 y.lag2 y.lag3
## 1 1 NA NA NA
## 2 2 1 NA NA
## 3 3 2 1 NA
## 4 4 3 2 1
## 5 5 4 3 2
## 6 6 5 4 3
## 7 7 6 5 4
## 8 8 7 6 5
## 9 9 8 7 6
## 10 10 9 8 7
## 11 11 10 9 8
## 12 12 11 10 9
matplot(x = px, y = d, type = 'o', lty = 1:4, col = 1:4, pch = 1:4,
main = '原系列とラグ系列', xlab = '時刻', ylab = '値')
grid()
legend('topleft', lty = 1:4, col = 1:4, pch = 1:4,
legend = c('原系列', '1次ラグ系列', '2次ラグ系列', '3次ラグ系列'))