arfit: Univariate AR Model Fitting

In TSSS: Time Series Analysis with State Space Model

Univariate AR Model Fitting

Description

Fit a univariate AR model by the Yule-Walker method, the least squares (Householder) method or the PARCOR method.

Usage

arfit(y, lag = NULL, method = 1, plot = TRUE, ...)

Arguments

y	a univariate time series.
lag	highest order of AR model. Default is 2 \sqrt{n}, where n is the length of the time series y.
method	estimation procedure. 1 : Yule-Walker method 2 : Least squares (Householder) method 3 : PARCOR method (Partial autoregression) 4 : PARCOR method (PARCOR) 5 : PARCOR method (Burg's algorithm)
plot	logical. If TRUE (default), PARCOR, AIC and power spectrum are plotted.
...	graphical arguments passed to the plot method.

Value

An object of class "arfit" which has a plot method. This is a list with the following components:

sigma2	innovation variance.
maice.order	order of minimum AIC.
aic	AICs of the estimated AR models.
arcoef	AR coefficients of the estimated AR models.
parcor	PARCOR.
spec	power spectrum (in log scale) of the AIC best AR model.
tsname	the name of the univariate time series y.

References

Kitagawa, G. (2020) Introduction to Time Series Modeling with Applications in R. Chapman & Hall/CRC.

Examples

# Sunspot number data
data(Sunspot)
arfit(log10(Sunspot), lag = 20, method = 1)

# BLSALLFOOD data
data(BLSALLFOOD)
arfit(BLSALLFOOD)

TSSS documentation built on Sept. 29, 2023, 9:07 a.m.