David Villegas Ríos <chirleu <at> gmail.com> writes: > Hi, > For a number of individuals, I have measured several behavioral traits in > the wild. Those traits (e.g. home range) can be estimated on different > temporal scales, for example daily, weekly or monthly. I want to estimate > repeatability of those traits, assuming that the daily/weekly/monthly > measurements represent replicates. I have 3 months (90 days) of data for > each trait. Two questions: > > 1) How can assess if there is temporal autocorrelation in my model? I guess > that if I consider daily measurements as replicates (90 replicates), I will > have some autocorrelation, but if I use just monthly measurements (3 > replicates) maybe I avoid it. > > 2) How can account for temporal autocorrelation in MCMCglmm? > > Sorry for this pretty basic questions but I haven't found an answer so far.
You'll probably be better off asking this question at r-sig-mixed-models (at) r-project.org. As a first pass, you might be able take the residuals from your fit and use acf() to compute the autocorrelation function. Actually, though, you'll probably be better off fitting a 'null' lme() model (fixed=resid~1, random=~1|individual) and then using the ACF() method (not the same thing as acf()) on the resulting model fit. Ben Bolker ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.