fpeaut: FPE Auto

In timsac: Time Series Analysis and Control Package

FPE Auto

Description

Perform FPE(Final Prediction Error) computation for one-dimensional AR model.

Usage

  fpeaut(y, max.order = NULL)

Arguments

y	a univariate time series.
max.order	upper limit of model order. Default is 2 \sqrt{n}, where n is the length of the time series y.

Details

The AR model is given by

y(t) = a(1)y(t-1) + .... + a(p)y(t-p) + u(t)

where p is AR order and u(t) is a zero mean white noise.

Value

ordermin	order of minimum FPE.
best.ar	AR coefficients with minimum FPE.
sigma2m	= sigma2(ordermin).
fpemin	minimum FPE.
rfpemin	minimum RFPE.
ofpe	OFPE.
arcoef	AR coefficients.
sigma2	\sigma^2.
fpe	FPE (Final Prediction Error).
rfpe	RFPE.
parcor	partial correlation.
chi2	chi-squared.

References

H.Akaike and T.Nakagawa (1988) Statistical Analysis and Control of Dynamic Systems. Kluwer Academic publishers.

Examples

y <- arima.sim(list(order=c(2,0,0), ar=c(0.64,-0.8)), n = 200)
fpeaut(y, max.order = 20)

timsac documentation built on Sept. 30, 2023, 5:06 p.m.