FPE: Final Prediction Error Criterion

In bvhar: Bayesian Vector Heterogeneous Autoregressive Modeling

Final Prediction Error Criterion

Description

Compute FPE of VAR(p) and VHAR

Usage

FPE(object, ...)

## S3 method for class 'varlse'
FPE(object, ...)

## S3 method for class 'vharlse'
FPE(object, ...)

Arguments

object	Model fit
...	not used

Details

Let \tilde{\Sigma}_e be the MLE and let \hat{\Sigma}_e be the unbiased estimator (covmat) for \Sigma_e. Note that

\tilde{\Sigma}_e = \frac{n - k}{T} \hat{\Sigma}_e

Then

FPE(p) = (\frac{n + k}{n - k})^m \det \tilde{\Sigma}_e

Value

FPE value.

References

Lütkepohl, H. (2007). New Introduction to Multiple Time Series Analysis. Springer Publishing.

bvhar documentation built on April 4, 2025, 5:22 a.m.