R: FPE Auto

fpeaut {timsac} | R Documentation

## 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)

[Package timsac version 1.3.5 Index]