Hello Peter, You haven't included the plate factor in the formula in the glmm statement, it should be: glmm(formula=cbind(r,n-r) ~ x1 + x2 + plate, data=seeds, ....) I thought I had sorted out the problem of models with no random terms, but clearly I hadn't, so sometime I must try to fix this. Since GLMMGibbs uses flat priors for fixed effects, the Credible intervals for effects in a model with no random effects will be equal to the frequentist confidence intervals produced by glm() Best Wishes Jonathan Myles
On Thu, 30 Aug 2001, Peter Baker wrote:
Hi all I know GLMMGibbs is still in beta but has anyone experienced (and solved ;-) this problem? I decided to look at the seeds example but I get a core dump on two intel linux boxes and also a sun workstation. All are running R1.3.0 but different hardware/OS's so I think I've done something wrong
library(GLMMGibbs) data(seeds) seeds$plate <- as.factor(1:21) seeds$plate <- Ra(data=seeds$plate, shape=0.001, scale=0.001,
+ type="identity", contrast="sum", of.interest=F)
gseeds.1 <- glmm(formula=cbind(r,n-r) ~ x1 + x2, data=seeds, family=binomial,
+ store.results=T, icm=500, burnin=1000, keep=20000, + progress.info=500, thin=5) Segmentation fault (core dumped)
version
_ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 3.0 year 2001 month 06 day 22 language R $ cat /etc/issue Red Hat Linux release 6.2 (Zoot) Kernel 2.2.16-3 on an i686 Suggestions welcome Thanks Peter -- Dr Peter Baker, Statistician (Bioinformatics/Genetics), CSIRO Mathematical & Information Sciences, 233 Middle St/ PO Box 120, CLEVELAND, QLD 4163 Australia. Email: Peter.Baker at cmis.csiro.au Phone:+61 7 3826 7263 Fax:+61 7 3826 7304
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