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.
--
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
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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