ARIMA - 統合型ARMA

Rで学ぶARIMAモデル

David Stoffer

Professor of Statistics at the University of Pittsburgh

ARIMAの識別

差分後のデータがARMAなら、元の時系列はARIMAである

# Simulation  ARIMA(p = 1, d = 1, q = 0)
x <- arima.sim(list(order = c(1, 1, 0),  ar = .9), n = 200)
plot(x, main = "ARIMA(p = 1, d = 1, q = 0)")
plot(diff(x), main = "ARMA(p = 1, d = 0, q = 0)")

ch3_1.012.png

統合ARMAのACFとPACF

x <- arima.sim(list(order = c(1, 1, 0),  ar = .9), n = 200)
acf2(x)

ch3_1.015.png

差分後ARIMAのACFとPACF

x <- arima.sim(list(order = c(1, 1, 0),  ar = .9), n = 200)
acf2(diff(x))

ch3_1.018.png

差分後ARIMAのACFとPACF

x <- arima.sim(list(order = c(1, 1, 0),  ar = .9), n = 200)
acf2(diff(x))

ch3_1.019.png

週間原油価格

ch3_1.021.png

週間原油価格

ch3_1.022.png

ARIMA(1, 1, 1) に見える

演習に進みましょう！

Rで学ぶARIMAモデル