White noise (WN) मॉडल

R में Time Series Analysis

David S. Matteson

Associate Professor at Cornell University

White noise

White Noise (WN) एक stationary प्रक्रिया का सबसे सरल उदाहरण है.

एक weak white noise प्रक्रिया में होता है:

White Noise के time series plots:

White Noise के time series plots?

# 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

R में Time Series Analysis