On Tue, 3 Mar 2015, Riccardo (Jack) Lucchetti wrote:

On Tue, 3 Mar 2015, Allin Cottrell wrote:

I was thinking along the same lines as in your patch for library.c in the GUI, but it's not that simple. Two things have to be answered.

1) What's the appropriate generalization of "m-p-q" for cases such as "gappy" arma and seasonal arma? Is it just the total number of AR and MA coefficients estimated?

Yes, I agree, this is why I inserted the comment line

   /* probably wrong but just for testing by now */

However, this is no more wrong than what we were doing before and arguably right in the most common cases.

2) What should we do with our current table of results, which shows ACF, PACF, Q statistic and p-value from m = 1 up to a specified maximum lag? Obviously we can't show a p-value when the df is < 0. Should we suppress all of the rows until m is large enough that df > 0, or just not print Q + p-value for the initial rows?

Good point. We may want to drop the Qs for the firs m rows, the rationale being: the sample autocorrelations (either total and partial) are statistics which can be given a descriptive interpretation, so there's no reason to drop them. That said, they also form the basis for the Q statistic, which is probably only worth reporting when it can be given a meaningful interpretation as a test statistic (that is, when df>0).

OK, that's now done in CVS and snapshots (print ACF and PACF "all the way", but Q and p-value only when df > 0).

--

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