similar to: mixed effects models - negative binomial family?

Hi, I am hoping some one can help with this. I am using nlme to fit a random coefficients model. It ran for hours before returning Error: Singularity in backsolve at level 0, block 1 The model is > plavix.nlme<-nlme(PLX_NRX~loglike(PLX_NRX,PD4_42D,GAT_34D,VIS_42D,MSL_42D,SPE_ROL,XM2_DUM,THX_DUM,b0,b1,b2,b3,b4,b5,b6,b7,alpha), + data=data, + fixed=list(b0 +

Hello, I am having trouble loading Matrix (0.96-3) in self-compiled R-2.1.1- beta, and self compiled R.app (got it a couple of days ago via: svn co https://svn.r-project.org/R-packages/trunk/Mac-GUI Mac-GUI ) on Mac OS 10.4.1. The problem I get when I try to load Matrix is the following: (I know I do not need to worry about the warnings, even though it might be nice to know why they

Hello all, This may be aimed for r-devel, but I encountered this as an R-user and not an R-developer so I start here (having said that, please direct me to R-devel if you think this is appropriate. I am not cross- posting, as I believe this is bad netiquette). I am a recent, but extremely happy R-user (especially after getting my own copy of MASS 2002). My adventures started when I wanted

Dear all (copying the package author), I have a question on the vlmc package. I am trying to model a time series, where each element can take one of 11 values (the result of some clustering). When I run the following command (synthetic data to facilitate self-contained example) I get the following warning: ("alphabet with >1-letter strings; trying to abbreviate") +++ START+++ >

Let me redirect the topic a bit. I've been considering unbundling gregmisc. The pro would be that people would find the component packages (i.e. gdata) more easily. The con is that the packages have a number of interdependencies, so you pretty much will need to get most of them anyway. As the latest gregmisc bundle contains a gregmisc package that is just a stub that depends on and loads

Let me redirect the topic a bit. I've been considering unbundling gregmisc. The pro would be that people would find the component packages (i.e. gdata) more easily. The con is that the packages have a number of interdependencies, so you pretty much will need to get most of them anyway. As the latest gregmisc bundle contains a gregmisc package that is just a stub that depends on and loads

Hi, I have a linux SuSE 8.1 with samba 2.2.5 Release 80. I have a Windows XP Professional that is member of a Samba domain, authentication it's OK but i have a profile in /usr/lib/samba/netlogon that i want to execute when the XP boots, i don't know what's happening. I have read the "How to" documentation Can you help me, please? Thanks a lot.

Hey, Does anyone know if there is a way to get back from goodfit what it estimated the parameters to be? I used the code fit<-goodfit(round(data$PLX_NRX),type="nbinomial" and got a pretty good fit. I could not however duplicate this good fit with any parameter estimates that I had. Any ideas??? Thanks, Elizabeth Lawson ---------------------------------

Dear all I am tryiing to fit the following lme with an ARMA correlation structure: test <- lme(fixed=fev1f~year, random=~1|id2, data=pheno2, correlation=corARMA(value=0.2, form=~year|id2), na.action=na.omit) But I get the following error message: Error in getGroupsFormula.default(correlation, asList = TRUE) : "Form" argument must be a formula I have used this same form

Hi WizaRds, I'd like to overplot UK fuel consumption per quarter over the course of five years. Sounds simple enough? Unless I'm missing something, the following seems very involved for what I'm trying to do. Any suggestions on simplifications? The way I did it is awkward mainly because of the first call to plot ... but isn't this necessary, especially to set limits for the

Hello, I am a new R user and I am trying to estimate some generalized linear models (glm). I am trying to compare a model with a gaussian distribution and an identity link function, and a poisson model with a log link function. My problem is that while the gaussian model has significantly lower (i.e. "better") AIC (Akaike Information Criterion) most of the coefficients are not

Hi, i am trying to run an ANCOVA and a bootstrapped ANCOVA analysis on a specific data set. I am using the ancova and ancboot functions as in the following code: setwd("C:/Users/User/Desktop/Rdatabilingualstudy2012") bilingualismdata<-read.spss("bilingualdataforconferences2012.sav", use.value.labels = TRUE, to.data.frame = TRUE)

Dear R-helpeRs, I was not sure if this is ESS-specific or Mac-specific etc, so I send in the main list. I had the setup emacs+ess+R 2.2.1 running fine (on a powerbook G4). I recently upgraded R to 2.3.0 and it runs fine from the GUI and from the terminal. However, when I try to run it from emacs (which was running fine with R2.2.1) I get the "Process R is not running" message.

Hello, I have a problem concerning estimation of GLMM. I used methods from 3 different packages (see program). I would expect similar results for glmm and glmmML. The result differ in the estimated standard errors, however. I compared the results to MASS, 4th ed., p. 297. The results from glmmML resemble the given result for 'Numerical integration', but glmm output differs. For the

I'm trying to use the glmmML package on a Windows machine. When I try to install the package, I get the message: > {pkg <- select.list(sort(.packages(all.available = TRUE))) + if(nchar(pkg)) library(pkg, character.only=TRUE)} Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library

Dear all, This question is basic but I am stumped. After running the below, I receive the message: "non-integer #successes in a binomial glm!" model1 <- glmmML(y~Brood.Size*Density+Date.Placed+Species+Placed.Emerging+Year+rate.of.parperplot, data = data, cluster= data$Patch, family=binomial(link="logit")) My response variable is sex ratio, and I have learned quickly not

A new version, 0.65-1, of glmmML is now on CRAN. It is a major rewrite of the inner structures, so frequent updates (bug fixes) may be expected for some time. News: * The Laplace and adaptive Gauss-Hermite approximations to the log likelihood function are fully implemented. The Laplace method is made the default. It should give results you can compare to the results from 'lmer' (for the

A new version, 0.65-1, of glmmML is now on CRAN. It is a major rewrite of the inner structures, so frequent updates (bug fixes) may be expected for some time. News: * The Laplace and adaptive Gauss-Hermite approximations to the log likelihood function are fully implemented. The Laplace method is made the default. It should give results you can compare to the results from 'lmer' (for the

Greetings. Here is sample code, with some comments. It shows how I can simulate data and estimate glm with binomial family when there is no individual level random error, but when I add random error into the linear predictor, I have a difficult time getting reasonable estimates of the model parameters or the variance component. There are no clusters here, just individual level responses, so

Hi, I have a spatial data set with many observations (~50,000) and would like to keep as much data as possible. There is spatial dependence, so I am attempting a mixed model in R with a spherical variogram defining the correlation as a function of distance between points. I have tried nlme, lme, glmmML, and glmmPQL. In all case the matrix needed (seems to be (N^2)/2 - N) is too large for my