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 [EMAIL PROTECTED] +44 (0)20 8525 0696 http://www.burns-stat.com (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 > > > >>1-pchisq(value,correctdf) >> >> > > >Nestor >(R 2.2.1 on Linux, Suse 9.3) > > > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html