Analisis Deret Waktu dengan R
David S. Matteson
Associate Professor at Cornell University
White Noise (WN) adalah contoh paling sederhana dari proses stasioner.
Proses weak white noise memiliki:
Plot runtun waktu untuk White Noise:

Plot runtun waktu untuk White Noise?

# Simulate n = 50 observations from the WN model
WN_1 <- arima.sim(model = list(order = c(0, 0, 0)), n = 50)
head(WN_1)
-0.005052984 0.042669765 3.261154066
2.486431235 0.283119322 1.543525773
ts.plot(WN_1)

# Simulate from the WN model with mean = 4, sd = 2
WN_2 <- arima.sim(model = list(order = c(0, 0, 0)),
n = 50, mean = 4, sd = 2)
ts.plot(WN_2)

# Fit the WN model with
# arima()
arima(WN_2,
order = c(0, 0, 0))
Coefficients:
intercept
4.0739
s.e. 0.2698
sigma^2 estimated as 3.639
# Calculate the sample
# mean and sample variance
# of WN
mean(WN_2)
4.0739
var(WN_2)
3.713
Analisis Deret Waktu dengan R