On Jul 7, 2011, at 22:21 , Prof Brian Ripley wrote: > On Thu, 7 Jul 2011, peter dalgaard wrote: > >> >> On Jul 7, 2011, at 19:52 , Prof Brian Ripley wrote: >> >>> Yes, ar and arima are using different estimation methods: arima is mle >>> whereas the default is method-of-moments. >>> >>> With such a large ar coefficient the end effects will matter, and the mle >>> (done by arima or ar.mle or ar(method="mle")) is the more accurate method >>> since it makes maximal use of the ends of the series. >> >> Yes, but... >> >> MLE also has subtly stronger assumptions, namely that the whole series is >> stationary. This boils down to the first observation(s) having the >> stationary mean and variance. This is not always the case if, e.g., the >> system is measured following some initial perturbation. > > But Yule-Walker (as distinct from OLS) also makes that assumption. >
Right. I was thinking of the conditional MLE given the first p observations, which AFAIR is equivalent to regressing on the lagged values (except probably for the residual df). -- Peter Dalgaard Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
