fpeaut {timsac}

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)