White noise process (time_series_model)

Constructs a time_series_model for white noise with variance sigma2. The process is defined as \(X_t \stackrel{\text{i.i.d.}}{\sim} N(0, \sigma^2)\) with autocovariance \(\gamma(h) = \mathrm{cov}(X_t, X_{t+h}) = \sigma^2 \mathbf{1}\{h=0\}\)

wn(sigma2 = NULL)

Arguments

sigma2

Innovation variance (> 0).

Value

A time_series_model object.

Examples

mod <- wn(sigma2 = 1)
mod
#> Stochastic process
#>   Model      : White Noise 
#>   Parameters : sigma2 =     1