similar to: glmmADMB and the GPL -- formerly-- How to buy R.

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

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

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,

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

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

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

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

Dear all, I am having some problems trying to run a GLMM model with zero-inflation using the alpha version of glmmADMB (0.6.4) using R (2.13.1) in Windows and I would greatly appreciate some help. My count response variable (number of birds: count) fits a negative binomial distribution and the explanatory variables are both continuous and categorical (species= 17). The three random effects are

Dear R-users, A recent post (Feb 16) to R-help inquired about fitting a glmm with a negative binomial distribution. Professor Ripley responded that this was a difficult problem with the simpler Poisson model already being a difficult case: https://stat.ethz.ch/pipermail/r-help/2005-February/064708.html Since we are developing software for fitting general nonlinear random effects models we

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

Dear All, As you know, glmmADMB package use ML method for estimation. Is it possible to use REML estimation method for zero-inflated Poisson distribution? For ML method, poi_ML <- glmm.admb(los ~ psihigh + trt.mod + trt.high + psihigh*trt.mod + psihigh*trt.high + 1, random = ~1, group="site", family="poisson", data=edcap) summary(poi_ML) How can I control to use REML

Dear R-list, I thought that I would let some of you know of a free R package, glmm.ADMB, that can handle mixed models for overdispersed and zero-inflated count data (negativebinomial and poisson). It was built using AD Model Builder software (Otter Research) for random effects modeling and is available (for free and runs in R) at: http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html I

I am using the 'glmmPQL function in the 'MASS' library to fit a mixed effects logistic regression model to simulated data. I am conducting a series of simulations, and with certain simulated datasets, estimation of the random effects logistic regression model unexpectedly terminates. I receive the following error message from R: Error in lme.formula(fixed=zz + arm.long,random=~1 |

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

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

There has recently been some discussion on the list about AD Model builder and the suitability of R for constructing the types of models used in fisheries management. https://stat.ethz.ch/pipermail/r-help/2006-January/086841.html https://stat.ethz.ch/pipermail/r-help/2006-January/086858.html I think that many R users understimate the numerical challenges that some of the typical

Hi I am running an lmer which works fine with family=poisson mixed.model<-lmer(nobees~spray+dist+flwabund+flwdiv+round+(1|field),family="poisson",method="ML",na.action=na.omit) But it is overdispersed. I tried using family=quasipoisson but get no P values. This didnt worry me too much as i think my data is closer to negative binomial but i cant find any examples of

Dear R users, Does anyone know how to get standard errors of the parameter estimates in glmm.admb? Thanks, Istvan

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

[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