On 07/11/2012 13:00, r-sig-mixed-models-request at r-project.org wrote:
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https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models or, via email, send a message with subject or body 'help' to r-sig-mixed-models-request at r-project.org You can reach the person managing the list at r-sig-mixed-models-owner at r-project.org When replying, please edit your Subject line so it is more specific than "Re: Contents of R-sig-mixed-models digest..." Today's Topics: 1. corARMA in lme (Arnaud Mosnier) 2. Re: lmer: effects of forcing fixed intercepts and slopes (Gjalt-Jorn Peters) 3. Re: lmer: effects of forcing fixed intercepts and slopes (ONKELINX, Thierry) ---------------------------------------------------------------------- Message: 1 Date: Tue, 6 Nov 2012 12:59:19 -0500 From: Arnaud Mosnier <a.mosnier at gmail.com> To: "r-sig-mixed-models at r-project.org" <r-sig-mixed-models at r-project.org> Subject: [R-sig-ME] corARMA in lme Message-ID: <CANkFkEd3ph3pLw-yUpRXCk3U=GMsgFqR-Qneh5BF8Xx4m1dFHg at mail.gmail.com> Content-Type: text/plain Dear mixed-models useRs, I made a mixed model of the form lme(Distance ~ season, random = ~1|yearTagged/tag, correlation = corAR1(form= ~Time|yearTagged/tag), data = dat) or lme(Distance ~ season, random = ~1|yearTagged/tag, correlation = corARMA(form= ~Time|yearTagged/tag, p=1, q=1), data = dat) In the AR1 model, the Phi value obtained for the corAR1 structure is 0. In the ARMA(1,1) model, both Phi1 and Theta1 are equal to 0. I find this strange. I believed first that it was caused by the fact that yearTagegd and tag variables were not considered as factor, but it did not change anything if I convert them to factor. The temporal autocorrelation is not obvious in the residuals of the model without a temporal structure included (i.e. without corAR1 or corARMA), but can I conclude that there is not correlation based on Phi value ?
Arnaud...no you cannot conclude that. The random effect structure is already imposing a correlation on the data from the same tag, and also on data from the same yearTagged. Phi alone does not quantify your correlation. The ARMA is trying to add extra correlation. On top of that..the AR and ARMA correlation structures are quite specific. If you think that there should be correlation, try different starting values for the phi. Alain
Thanks for your help, Arnaud [[alternative HTML version deleted]]
Dr. Alain F. Zuur First author of: 1. Analysing Ecological Data (2007). Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p. URL: www.springer.com/0-387-45967-7 2. Mixed effects models and extensions in ecology with R. (2009). Zuur, AF, Ieno, EN, Walker, N, Saveliev, AA, and Smith, GM. Springer. http://www.springer.com/life+sci/ecology/book/978-0-387-87457-9 3. A Beginner's Guide to R (2009). Zuur, AF, Ieno, EN, Meesters, EHWG. Springer http://www.springer.com/statistics/computational/book/978-0-387-93836-3 4. Zero Inflated Models and Generalized Linear Mixed Models with R. (2012) Zuur, Saveliev, Ieno. http://www.highstat.com/book4.htm Other books: http://www.highstat.com/books.htm Statistical consultancy, courses, data analysis and software Highland Statistics Ltd. 6 Laverock road UK - AB41 6FN Newburgh Tel: 0044 1358 788177 Email: highstat at highstat.com URL: www.highstat.com URL: www.brodgar.com