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Dear colleagues, I am interested in applying Bayesian inference to non-linear quantile regression models, but I couldn't find any facilities for this in R. Any clues on packages/functions, or anything else? Thanks in advance, Pedro A. C...

I was trying to install e1071 and the compilation failed. Can some of you R gurus help me with this... thanks pedro ---- Installing package `e1071' ... libs gcc -g -fpic -I/usr/local/R/include -c pgm.c -o pgm.o...

I was trying to make some multi figure plots and I had some strange problems. I'm using R 0.61.2. When I make this plot >postscript(file="timeplot5.ps",horizontal=TRUE) >par(mfrow=c(2,2)) >plot(dados...

I've been playing with R for a while using emacs ESS. I've started to like it a lot ( the beautiful S language was unknown to me before I dumped into R) I want to make some scripts to...

Hi Brian, a simple approach would be to summarize species composition using some ordination method (e.g. PCoA) and then use it as a response variable in a linear model where the predictors would be the environmental gradient and region...

Hi, you could ordinate your observations first (e.g. using NMDS or PCoA), and then model the resulting scores using location and time as predictors (if you are interested in estimating their independent effects), or using a repeated-measures Anova...

Hi, Fernando. The warning message "In mer_finalize(ans) : gr cannot be computed at initial par (65)" points to problems during the iterative process of model fitting. This may be caused by the complexity of the global model you're...

Tim and Chris, I think zero-inflated linear models for presence/absence data could be implemented with package "vgam", but I have never tried it. Regards 2011/8/25, cparker at pdx.edu <cparker at pdx.edu>: > Tim pointed put...

Hi Tim, there are several ways of dealing with spatial autocorrelation in ecological models (see e.g. Dormann 2007: Methods to account for spatial autocorrelation in the analysis of species distributional data: a review; and Beale et al. 2010: Regression...

Dear Rick, I believe the error occurs because the "time" covariate in the correlation structure cannot have repeated values; these functions assume that you have a single observation for each time step. The simplest solution is to create a time...

Hi Johannes, I think your approach is reasonable. As you pointed out, however, generating such parameter distributions as you did is not strictly the same as bootstraping. The bootstrap simulates repeated sampling from one original, target population, by assuming the...

Dear Richard, your question could be handled using a linear model incorporating a temporal autcorrelation structure within trees. However, I don't think using "tree" as random factor (e.g. in lme()) would be very helpful here because random factors...