similar to: help with glmmADMB ZI; function maximizer failed

Hello everybody, I am using glmmADMB and when I run some models, I recieve the following message: Erro em glmmadmb(eumencells ~ 1 + (1 | owners), data = pred3, family = "nbinom", : The function maximizer failed (couldn't find STD file) Furthermore: Lost warning messages: Command execution 'C:\Windows\system32\cmd.exe /c

Hi there, I am new to the package glmmadmb, but need it to perform a zero-inflated gzlmm with a binomial error structure. I can't seem to get it to work without getting some strange error messages. I am trying to find out what is affecting the number of seabird calls on an array of recorders placed at 4 sites on 6 islands. I have nightly variables (weather and moonlight), site variables

Greetings glmmADMB function users, I am trying to run a series of models using the glmmADMB function with several different distribution families (e.g., poisson, negbinom). I am using a Optiplex 790 PC with Windows 7, 16.0 GB of RAM and a 64-bit operating system. I am running R version 2.15.0 and started out using the most recent version of glmmADMB (I believe version 7.2.15). My data is zero

[cc'ed back to r-help] I've started to take a look, and there's nothing immediately obvious about the problem with the fit (the warnings and errors are about a "non-positive-definite Hessian", which usually means an overfitted/poorly identified model) -- still working on whether there's a way to get more useful information. As it turns out, glmmADMB's default

library(glmmADMB) #Example for glmm.admb data(epil2) glmm.admb(y~Base*trt+Age +Visit,random=~Visit,group="subject",data=epil2,family="nbinom") Gives: Error in glmm.admb(y ~ Base * trt + Age + Visit, random = ~Visit, group = "subject", : The function maximizer failed ****************** R version 2.4.1 RC (2006-12-14 r40181) powerpc-apple-darwin8.8.0 locale: C

Hi R-users,   I intend to apply a mixed model on a set of longitudinal data, with a negative binomial distributed dependent variable, and after following the discussions on R help list I saw that more experienced people recommended using lmer (from lme4 pack), glmmPQL (from MASS) or glmm.admb (from glmmADMB pack)     My first problem: yesterday this syntax was ok, now I get this weird message (I

After copy and pasting the code for installation of glmmADMB package suggested at http://glmmadmb.r-forge.r-project.org/, I receive this message. > install.packages("glmmADMB", repos="http://r-forge.r-project.org",type="source") Warning message: In getDependencies(pkgs, dependencies, available, lib) : package 'glmmADMB' is not available I'm not

Dear R-users, Half a year ago we put out the R package "glmmADMB" for fitting overdispersed count data. http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html Several people who used this package have requested additional features. We now have a new version ready. The major new feature is that glmmADMB allows Bernoulli responses with logistic and probit links. In addition there

Dear List, Some of you have been following the discussion of the GPL and its inclusion in the glmmADMB package we created for R users. I would like to provide a bit of background and include an email we received from Prof. Ripley so that everyone can be aware of how some might use the GPL to try to force access to proprietary software. I think this is interesting because many have voiced the

Hi here, i recently notice the software built by otter company know as AD-MB tools . i explore a little bit this tools under the R Package for mixed logistics model. it is a very interesting tool. but i get several questions. first question: i tried the R code below, and have the error , i can run the code for switching the setting to impSamp=0 , it means i can only run the code under

dear R-users, I have to model counts where all counts above some threshold have been censored. In the same dataset I have too many zeroes for a Poisson or even a negative binomial distribution to make sense, so I would need a zero-inflated-censored negative binomial family for use in glmer (or glmmADMB?). That seems not to exist. my question is : how could I add a custom-built family of

I am attempting to build a package on r-forge and running into a weird error. I have been in correspondence with the R-forge admins and am turning to r-devel on the remote chance that someone might have a guess as to what is going wrong or a suggestion about further diagnostics/experiments I could try ... The package seems to build fine on my system(s) with R CMD build --compact-vignettes

Dear R-users, Earlier this year I posted a message to this list regarding negative binomial mixed models in R. It was suggested that the program I had written should be turned into an R-package. This has now been done, in collaboration with David Fournier and Anders Nielsen. The R-package glmmADMB provides the following GLMM framework: - Negative binomial or Poisson responses. - Zero-inflation

The freely available R package glmmADMB can do Adaptive Gaussian Quadrature for this type of model, since it is built using AD Model Builder's random effects module which incorporates this feature. There is now a beta version of the software for people using R on the Mac intel platform. http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html Cheers, Dave -- David A. Fournier

Hello, I was wondering if weighting has been added to glmmadmb as of yet? I found a post about a year ago that it it hadn't been implemented yet but I was hoping the documentation may just have not yet caught up. Thanks, Trevor Davies [[alternative HTML version deleted]]

R glmmADMB question I am trying to use glmm.admb (the latest alpha version from the R forge website 0.6.4) to model my count data that is overdispersed using a negative binomial family but keep getting the following error message: Error in glmm.admb(data$total_bites_rounded ~ age_class_back, random = ~food.dif.id, : Argument "group" must be a character string specifying the

Hola! Estoy con un problema con mis datos, tengo datos de abundancia y tengo que analizarlas con glmm. Uso la función glmmadmb() del paquete glmmADMB de R, que acepta varias familias de distribución. El problema es que al hacer los modelos, no me muestra el residual deviance ni los grados de libertad, para poder calcular la overdispersión. Alguien sabe cómo puedo calcularla en esa función? o con

Hello, I hate to ask a question which is directly addressed in the documentation, but can someone please give me an example of how to change the maximum number of iterations used by lmer. I'm having a hard time understanding this: control a list of control parameters. See below for details. control a named list of control parameters for the estimation algorithm, specifying only

Dear list, I am having some problems with extracting Variance Components from a random-effects model: I am running a simple random-effects model using lme: model<-lme(y~1,random=~1|groupA/groupB) which returns the output for the StdDev of the Random effects, and model AIC etc as expected. Until yesterday I was using R v. 2.0, and had no problem in calling the variance components of the

Dear Dr Skaug and R users, just discovered glmm.admb in R, and it seems a very useful tool. However, I ran into a problem when I compare two models: m1<-glmm.admb(survival~light*species*damage, random=~1, group="table", data=bm, family="binomial", link="logit") m1.1<-glmm.admb(survival~(light+species+damage)^2, random=~1, group="table", data=bm,