est.ar.wge: Estimate parameters of an AR(p) model

In tswge: Time Series for Data Science

Estimate parameters of an AR(p) model

Description

Estimate parameters of an AR(p) with p assumed known. Outputs residuals (backcast0 and white noise variance estimate.)

Usage

est.ar.wge(x, p = 2, factor = TRUE, method = "mle")

Arguments

x	Realization
p	AR order
factor	If TRUE (default) a factor table is printed for the estimated model
method	Either "mle" (default), "burg", or "yw"

Details

The 'type' arument is added for backwards compatabililty and if specified will replace the value specified in the 'method' argument.

Value

method	Estimation method used: MLE, Burg, or YW
phi.est	Estimates of the AR parameters
res	Estimated residuals (using backcasting) based on estimated model
avar	Estimated white noise variance (based on backcast residuals)
xbar	Sample mean of data in x
aic	AIC for estimated model
aicc	AICC for estimated model
bic	BIC for estimated model

Author(s)

Wayne Woodward

References

"Applied Time Series Analysis with R, 2nd edition" by Woodward, Gray, and Elliott

Examples

data(fig6.1nf)
          est.ar.wge(fig6.1nf,p=1)

tswge documentation built on Feb. 16, 2023, 6:51 p.m.