rcAR: Estimating of Random-Coefficient AR Models

In NTS: Nonlinear Time Series Analysis

Estimating of Random-Coefficient AR Models

Description

Estimate random-coefficient AR models.

Usage

rcAR(x, lags = c(1), include.mean = TRUE)

Arguments

x	a time series of data.
lags	the lag of AR models. This is more flexible than using order. It can skip unnecessary lags.
include.mean	a logical value indicating whether the constant terms are included.

Value

rcAR function returns a list with following components:

par	estimated parameters.
se.est	standard errors.
residuals	residuals.
sresiduals	standardized residuals.

Examples

t=50
x=rnorm(t)
phi1=matrix(0.4,t,1)
for (i in 2:t){
   phi1[i]=0.7*phi1[i-1]+rnorm(1,0,0.1)
	x[i]=phi1[i]*x[i-1]+rnorm(1)
}
est=rcAR(x,1,FALSE)

NTS documentation built on Sept. 25, 2023, 1:08 a.m.