similar to: Mixed models

Hello Folks, Very new to R so bear with me, running 5.2 on XP. Trying to do a zero-inflated negative binomial regression on placental scar data as dependent. Lactation, location, number of tick larvae present and mass of mouse are independents. Dataframe and attributes below: Location Lac Scars Lar Mass Lacfac 1 Tullychurry 0 0 15 13.87 0 2 Somerset 0 0 0

Hello, I'm a bit new to the world of R so forgive my ignorance. I'm trying to do a zero-inflated negative binomial regression and have received an error message and i'm not sure what it means. I'm running R 2.5.1 on XP. I have just tried a really simple version of the model to see if it would run before I put all the variables in. I have attached all the variables to the

Dear All I am using the histogram() function to plot two subsets from my data on the same output display, i.e. there are two histogram plots My code is: histogram( ~ Age | Date, layout = c(1, 2), xlab = "Age (years)", strip = FALSE, strip.left = TRUE, col = "black", border = "white", cex.axis = 1.1, family = "serif", cex.lab =

Hey folks, I'm trying to do all subsets on a zero-inflated poisson regression. I'm aware of the leaps and regsubsets functions but I don't know if they work for ZIP regressions or how the syntax fits in for them. Can anyone help? The model syntax is: > zip.zc <- zicounts(resp=Scars~.,x=~Location + Lar + Mass + Lac + Lar:Mass + Location:Mass, data = alan2,

I have a user who is currently running R on a desktop system which takes 3 days to run. We have an Itanium 2 Cluster running HP UX. My system manager has tried to install R and has sent the following message INSTALL file says do ./configure make ./configure fails with ( tail end of output checking for main in -ltermcap... no checking for main in -ltermlib... no checking

Hi Ricky / AJ Progress of sorts. I got passed the last problem by looking at the makefiles but run in to the next one, see below. It has created files in /contrib/R-2.4.0. there is an " R " under /contrib/R-2.4.0/bin/R. Running it gives :- /contrib/R-2.4.0/bin/R R version 2.4.0 (2006-10-03) Copyright (C) 2006 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is

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

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

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 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:

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 All, Following Mike Praeger's posting on this list, I'm happy to pass on that AD Model Builder is now freely available from the ADMB Foundation. http://admb-foundation.org/ Two areas where AD Model builder would be especially useful to R users are multi-parmater smooth optimization as in larg scale maximum likelihood estimation and the analysis of general nonlinear random

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 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 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 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

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