wn: White noise process ('time_series_model')

In gmwmx2: Estimate Functional and Stochastic Parameters of Linear Models with Correlated Residuals and Missing Data

White noise process (time_series_model)

Description

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\}

Usage

wn(sigma2 = NULL)

Arguments

sigma2

Innovation variance (> 0).

Value

A time_series_model object.

Examples

mod <- wn(sigma2 = 1)
mod

gmwmx2 documentation built on June 10, 2026, 5:06 p.m.