Hi all,
Just to summarize the very helpful set of answers I got to my query
(see below for the problem description).
1) Specify a variance structure to account for heterogeneity of
residuals across different values of the explanatory variables (e.g.,
weights = varPower() in the lme() function the
Malin Pinsky writes:
> I'm having problems fitting a mixed-effects model for an ecological
> meta-analysis, and I'm curious if anyone has advice. In particular,
> it's pretty clear that the variance in the residuals increases with
> the predicted mean, but my normal fixes don't seem to be working
Algorithms for bayesian inference (MCMC) cannot run fast enough inside a
scripting language like R.
Most authors create plugins to call their fast binary (C/C++)
implementations inside of R. Just use them.
I recommend JAGS and rjags. Better errors messages and good support from
Plummer.
Cya
2012/
Dear list members,
This is not a very specific question on R for ecological analysis, but is
related.
I have been in courses where R and WinBugs are used together for data
analysis, however, I still don´t understand why R need to use WinBUGS to
perform some bayesian analysis.
I teach statistics
