[R] Degrees of freedom using Box.test()
narguea at uwf.edu
Wed Mar 8 16:48:32 CET 2006
It's Ljung and Box (1978) saying that for large number of observations a chi
squared with lags-p-q, should provide a good approximation "for most
practical purposes" (p. 298 of reference above).
On Wednesday 08 March 2006 4:00 am, Patrick Burns wrote:
> You are saying that the penalty on the degrees of freedom
> should be the same whether the model was fit with 100
> observations or 1 million observations. You are also saying
> that some tests should have negative degrees of freedom.
> So I don't think your proposal is the right answer, though
> presumably there should be some penalty.
> There is a working paper on the Burns Statistics website
> about robustness in Ljung-Box tests, but this issue is not one
> that is covered.
> Patrick Burns
> patrick at burns-stat.com
> +44 (0)20 8525 0696
> (home of S Poetry and "A Guide for the Unwilling S User")
> Nestor Arguea wrote:
> >After an RSiteSeach("Box.test") I found some discussion regarding the
> > degrees of freedom in the computation of the Ljung-Box test using
> > Box.test(), but did not find any posting about the proper degrees of
> > freedom.
> >Box.test() uses "lag=number" as the degrees of freedom. However, I
> > believe the correct degrees of freedom should be "number-p-q" where p and
> > q are the number of estimated parameters (for instance, in a Box-Jenkins
> > family of models). This, according to the main source in documentation of
> > Box.test:
> >G. M. Ljung and G. E. P. Box, On a measure of Lack of Fit in Time Series
> >Models, Biometrika, Vol. 65, No. 2 (August, 1978), pp. 297-303.
> >One can still compute the correct p-value with
> >(R 2.2.1 on Linux, Suse 9.3)
> R-help at stat.math.ethz.ch mailing list
> PLEASE do read the posting guide!
Nestor M. Arguea, Chair
Department of Marketing and Economics
University of West Florida
11000 University Parkway
Pensacola, FL 32514
More information about the R-help