similar to: AD Model Builder now freely available

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

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

Do Users of Nonlinear Mixed Effects Models Know Whether Their Software Really Works? Lesaffre et. al. (Appl. Statist. (2001) 50, Part3, pp 325-335) analyzed some simple clinical trials data using a logistic random effects model. Several packages and methods MIXOR, SAS NLMIXED were employed. They reported obtaining very different parameter estimates and P

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 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

De: Rubén Roa Enviado el: jueves, 17 de noviembre de 2011 9:53 Para: 'Users@admb-project.org' Asunto: Reporting a conflict between ADMB and Rtools on Windows systems Hi, I have to work under Windows, it's a company policy. I've just found that there is a conflict between tools used to build R packages (Rtools) and ADMB due to the need to put Rtools compiler's

Hi I'm trying to run an admb model from R by using the system () command. The admb model runs fine when running it from the admb command line or when using emacs. However when I try it with system() then R crashes every time. And I tried using the R command line and RGui and in both it crashes. I also tried it from different computers. What I do is I first set the directory where I keep

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

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

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,

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 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

Hello all, In a previous posting regarding glmm.admb it is stated that glmm.admb can handle 2 nested random effects. I can only fit a single random term at the moment, and wondered if anyone could provide me with some information on how to specify a model with 2 (nested or cross-classified) random terms? Thanks, Jarrod.

Hi I implemented the age-structure model in Gove et al (2002) in R, which is a nonlinear statistical model. However running the model in R was very slow. So Dave Fournier suggested to use the AD Model Builder Software package and helped me implement the model there. ADMB was incredibly fast in running the model: While running the model in R took 5-10 minutes, depending on the

X2R is a bundle of three software libraries for passing complicated data structures from Fortran, C/C++, or AD Model Builder to R. An update has been sent to CRAN and should be available from mirrors shortly. From the menu at the left of the CRAN home page, look under Software / Other. We also have updated FishGraph, a compatible set of R functions for examining output from fish population

X2R is a bundle of three software libraries for passing complicated data structures from Fortran, C/C++, or AD Model Builder to R. An update has been sent to CRAN and should be available from mirrors shortly. From the menu at the left of the CRAN home page, look under Software / Other. We also have updated FishGraph, a compatible set of R functions for examining output from fish population

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

Dear list, I am using optim() function to MLE ~55 parameters, but it is very slow to converge (~ 25 min), whereas I can do the same in ~1 sec. using ADMB, and ~10 sec using MS EXCEL Solver. Are there any tricks to speed up? Are there better optimization functions? Thanks Toshihide "Hamachan" Hamazaki, $B_@:j=S=((JPhD Alaska Department of Fish and Game:

Hello Folks, I'm after some help regarding mixed models. Basically I have sampled a number of different animals at 10 independent sites and am trying to create a mixed model to account for the variation between sites my current model looks like this: mm<-glmm.admb(Hep~Sex+Mass, random=~Mouse, group=Location, data=alan, family="binomial", link="logit") I numbered each

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