search for: glmmgibb

Hello, can anyone explain the following error I get when trying to use the CHECK command to check a new version of my pakcage under 1.4.0? ****** ./R CMD check ~/GLMMGibbs.0.5.1/GLMMGibbs * checking for working latex ... OK * using log directory `/homef/jonm/R-1.4.0/bin/GLMMGibbs.Rcheck' ... <Installs library, documentation, and then performs various tests, including the example, OK, then ...> * creating GLMMGibbs-manual.tex ... OK * checking GLMMG...

Dear all; Installing the GLMMGibbs package to my Solaris Unix box, I got an compiling error: ars.c:497:10: missing terminating " character ars.c: In function `dump_arse': ars.c:498: error: parse error before "mylesj" ..... The compiling error was reported to the list on Jul 3, 2003. According to Prof....

I getting compilation errors when trying to install GLMMGibbs (see below). I'm running R v 1.7.1 on SuSE Linux 8.2. Has anyone else had this problem? I tried it on a Win2000/R 1.5.1 combination and it worked fine. Any hints are greatly appreciated. Thank you in advance, Damien >install.packages("GLMMGibbs") trying URL `http://cran...

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...

Dear R-users, I wondered if anyone has extended GLMMGibbs to include correlated random effects, and if so, whether they would be willing to let me use their code? Jonathan Myles has no plans to extend glmm in this manner within the foreseeable future. With thanks, Patty -- ----------------------------------------------------------------------------...

Hello, I am trying to use glmm() in library GLMMGibbs, but I don't seem to have the package and it is not listed on CRAN. Is it no longer supported? (I am using R 2.1.1 on Windows.) Many thanks in advance for your help. Regards, Mark The information contained in this e-mail is confidential and...{{dropped}}

...ed to describe a rather amateurish approach to distributing software which may annoy some people, but I sincerely hope it doesn't. I've been working for some years with David Clayton on a project which started life as an S package but has now turned into an R library. It is (now) called GLMMGibbs and estimates the parameters of the Generalised Linear Mixed Model by Gibbs Sampling (using the Bayesian paradigm). The basic idea is that one declares a particular factor to be a random effect with one statement and then performs the Gibbs sampling with another statement with syntax somewhat lik...

Dear All, I wonder if there is a way to fit a generalized linear mixed models (for repeated binomial data) via a direct Maximum Likelihood Approach. The "glmm" in the "repeated" package (Lindsey), the "glmmPQL" in the "MASS" package (Ripley) and "glmmGIBBS" (Myle and Calyton) are not using the full maximum likelihood as I understand. The "glmmML" of Brostrom uses the "full maximum likelihood" by approximating the integral via Gauss- Hermite quadrature. However, glmmML is only valid for the random intercept model and the b...

...utcome variable (presence or absence of an attribute). As far as I can tell from reading archives of the R and S lists, as well as Pinheiro and Bates and Venables and Ripley, - nlme does not have the facility to do what amounts to a mixed-effects logistic regression. - The canonical alternative is GLMMgibbs, but there are concerns about this as well. - There has been some talk of wrappers around nlme that would add PQL (a technique about which I know nothing) as a way of estimating such equations. Does this accurately summarize the state of software availability? If not, what updates should I know a...

Happy new month, everyone! I am planning to write a NIH grant proposal to study ways to speed Monte Carlo based maximum likelihood algorithm for hierarchical models with a focus on generalized linear mixed models (GLM with random effects). I thought it would be nice and also increase the chance of funding if I could produce an R package in the process. I understand that Prof. Pinheiro ang Bates

...en.ac.at> License: GPL (see file COPYING), except for ./src/muin2ser.f and ./misc which are free for non-commercial purposes. See file README for details. URL: http://www.r-project.org Index of Contents (Text) Reference Manual (PDF) Package Sources AnalyzeFMRI CoCoAn Devore5 EMV GLMMGibbs GenKern GeneSOM KernSmooth Matrix NISTnls Oarray PHYLOGR PTAk RArcInfo RMySQL RODBC RPgSQL RandomFields RmSQL Rstreams Rwave SASmixed SuppDists VR XML acepack adapt akima ash bindata blighty boot bootstrap bqtl car cclust cfa chron cluster cmprsk coda conf.design cramer date diamonds dse e1071 ell...

...onse variable, binomial errors and multiple levels of nesting of random effects (e.g. site/block/quadrat/year), is there a package available which will do this? Jim Lindsey's package "repeated" appears to be only able to cope with 2 levels of nesting. Also I have been looking at the GLMMGibbs package but cannot locate the document "GLMMGibbs: An R Package for Estimating Bayesian Generalised Linear Mixed Models by Gibbs Sampling" which is supposed to be distributed with the package. Does anyone have this or can they tell me where to find it? Thanks, Yvonne Buckley ********...

...do is to describe spatio-temporal variation of homicide rates, identifying those combinations of province-year where the homicide rate is either over- or underrepresented based on Poisson expectation. Is it possible to carry out such an analysis with R? If so, what package should be preferred? GLMMGibbs, geoRglm, and function glmmPQL in MASS package sound as possible choices to me, but I'm no expert of this kind of analysis and I'd much appreciate any indication. Thank you very much for any help and best regards, Maurizio Pisati <><><><><><><&g...

Hello, I would like to know if there is any package that allow us to fit Generalized Linear Models via Maximum Likelihood and Linear Models using Generalized Least Squarse in R as the functions glim and gls, respectively, from S-Plus. Also, anybody know if there is any package that fit Log-Linear Models using Generalized Least Squares? Any help will be very useful. Thanks, -- Frederico

...rmation and graphics. >> >> I would appeciate your comments on the following points: >> >> 1. Is there a strong need for a package for generalized linear mixed >> models? Could someone have already written or in the process of writing >> one? > >See package GLMMgibbs on CRAN, function glmmPQL in package MASS and >function glmm (only a random intercept) in one of Jim Lindsey's packages. > >GLMMs are half a chapter in the upcoming fourth edition of Venables & >Ripley. > >> 3. How big is the undertaking? I have some R code for GLMM th...

Dear RHelpers, Does anyone know of any R code to perform bivariate Poisson regression (including random effects)? Best wishes Simon Simon D.W. Frost, M.A., D.Phil. Department of Pathology University of California, San Diego Antiviral Research Center (Formerly: UCSD Treatment Center) 150 W. Washington St., Suite 100 San Diego, CA 92103 USA Tel: +1 619 543 8080 x275 Fax: +1 619 298 0177 Email:

...less bias for finite samples. Of course, one can argue that Bayesian formulation automatically generates REML for variance components. Now the software. PQL and variations: GLME in beta by José Pinheiro, reglm by Gordon Smyth, glmmPQL in package MASS by Venables & Ripley Bayesian method: GLMMgibbs and BUGS (not a R or S-plus package). Standard MLE: glmm (only a random intercept) in one of Jim Lindsey's packages? Ok, this still leaves us without a good way of doing standard MLE. I have programmed standard MLE using R. It takes 6 minutes for a clustered binary outcome dataset, with 50...

I am trying to find a way to analyze a "simple" mixed model with two levels of a treatment, a random blocking factor, and (wait for it) negative binomial count distributions as the response variable. As far as I can tell, the currently available R offerings (glmmGibbs, glmmPQL in MASS, and Jim Lindsey's glmm code) aren't quite up to this. From what I have read (e.g. http://www.stat.ufl.edu/~jhobert/papers/nb7.ps), SAS PROC NLMIXED seems like the best way to go. I can go do that if I have to, but I'd prefer to do it in R if that seems feasible....

Hello, I would like to fit generalized linear mixed models but I did not find the package allowing such procedure. R help under nlme package gives me "glmmPQL(MASS)" but this file does not appear in contributed packages. Thanks in advance for your answer. Alexandre MILLON -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Tried to look for package GLLMGibbs-(package for fitting mixed models by Gibbs samppling contributed by Myles' and Clayton) in CRAN but not found it, Does anybody know if it is still available? thanks Oarabile