similar to: (lme4: lmer) mcmcsamp: Error in if (var(y) == 0)

I'm trying to use "predict" with a linear mixed-effects logistic regression model fitted with nlmmPQL from the MASS library. Unfortunately, I'm getting an error "non-conformable arguments" in predict.lme, and I would like to understand why. I have used the same call to "predict" with "glm" models without problems. I assume I'm doing

Hi, I'm having trouble with glmmPQL from the MASS package. I'm trying to fit a model with a binary response variable, two fixed and two random variables (nested), with a sample of about 200,000 data points. Unfortunately, I'm getting an error message that is difficult to understand without knowing the internals of the glmmPQL function. > model <- glmmPQL(primed ~

After upgrading to R 2.6.0, I'm having trouble running lmer: model <- lmer(primed ~ log(dist.time)*role + 1|target.utt, data=data.utts) Error in UseMethod("as.logical") : no applicable method for "as.logical" So I thought I'd upgrade lme4 to the latest version, but unfortunately the compilation fails - perhaps there's a missing #include: R CMD INSTALL

Hi the list. I try to learn the S4 programming. I find the wiki and several doc. But I still have few questions... 1. To define 'representation', we can use two syntax : - representation=list(temps = 'numeric',traj = 'matrix') - representation(temps = 'numeric',traj = 'matrix') Is there any difference ? 2. 'validityMethod' check the

I would like to add a class to the SparseM package. I have a class "matrix.csr" that describes a matrix in compressed sparse row format, now I would like a class matrix.diag.csr that describes such objects when they happen to be diagonal. The idea is that matrix.diag.csr objects should behave (later in life) exactly like matrix.csr objects, the distinction is only needed in order to

I have this https://echange-fichiers.inra.fr/get?k=6TdTdezNeZwAqJtpwVm grib file which is a regular lat-lon 0.25x0.25 degrees and contains 4 fields . I tried to open it using : grib <- readGDAL("C:\\Users\\aalyaari\\Desktop\\Vol_025_H14_2010060700.grib") but I got this error: C:\Users\aalyaari\Desktop\Vol_025_H14_2010060700.grib has GDAL driver GRIB and has 721 rows and

Dear all, My package has Depends: lme4.0 in the DESCRIPTION. I need to extract the fixed effect of a model and their standard errors. I use coef(summary(model)) inside a function to do that. Model is the output of a call to glmer() from the lme4.0 package. coef(summary(model)) throws an error: $ operator is invalid for atomic vectors I have tracked it down to a problem with summary(model)

Dear all, Maybe, I am doing something wrong, but using R-2.5.0 on my Intel-Mac, I have problems using function callNextMethod() in method initialize. I am loading the following code as file "testS4.R": setClass("baseClass", representation(myname = "character", mydir = "character", "VIRTUAL"),

Hi R community! I've fitted three mixed-effects regression models to a thousand bootstrap samples (case-resampling regression) using the lme4 package in a custom-built for-loop. The only output I saved were the inferential statistics for my fixed and random effects. I did not save any output related to the performance to the machine learning algorithm used to fit the models (REML=FALSE).

Hi all, I'm writing a script to do some basic text analysis in R. Let's assume I have a data frame named data which contains a column named 'utt' which contains strings. Is there a straightforward way to achieve something like this: data$ContainsThe <- ifelse(startsWith(data$Utt,"the"),"y","n") or data$ContainsThe <-

I'm using glmmPQL, and I still have a few problems with it. In addition to the issue reported earlier, I'm getting the following error and I was wondering if there's something I can do about it. Error in logLik.reStruct(object, conLin) : Na/NaN/Inf in foreign function call (arg 3) ... Warnings: 1: Singular precistion matrix in level -1, block 4 (...) 4: "" The

I really hope sombody could help me with the following, I'm having problems accessing the random effect samples following the example on MCMCsamp: (fm1 <- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy)) set.seed(101); samp0 <- mcmcsamp(fm1, n = 1000, saveb=TRUE) str(samp0) Formal class 'merMCMC' [package "lme4"] with 9 slots ..@ Gp :

Hi, I've got a linear mixed model created using lmer: A6mlm <- lmer(Score ~ division + (1|school), data=Age6m) (To those of you to whom this model looks familiar, thanks for your patience with this & my other questions.) Anyway, I was trying this to look at the significance of my fixed effects: A6post <- mcmcsamp(A6mlm, 50000) library(coda) HPDinterval(A6post) ..but I got this

Hi folks, I have assumed that ratios of variance components (Fst and Qst in population genetics) could be estimated using the output of mcmcsamp (the series on mcmc sample estimates of variance components). What I have started to do is to use the matrix output that included the log(variances), exponentiate, calculate the relevant ratio, and apply either quantile or or HPDinterval to get

Hello, I'm building a couple of mixed models using the lmer function. The actual modelling is going well, but doing some reading on the use of crossed random effects and the comparison of models with and without random effects it is clear that I need to generate some Markov Chain Monte Carlo samples. However, I'm struggling because everyone time I go to generate a sample I get the

I've searched the help archives of both lists and apologize if I missed the answer to my question: Is there an update on developing mcmcsamp for glmer? I'm using R v. 2.7.2 (on our Unix server - will hopefully be updated soon) and 2.8.1 on my PC and get the message for both: gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),family = binomial, data = cbpp)

Dear All, I've been using mcmcsamp() successfully with a few different mixed models but I can't get it to work with the following. Is there an obvious reason why it shouldn't work with a model of this structure ? *brief summary of objective: I want to test the effect of no-fishing marine reserves on the abundance of a target species. I have samples at coral reef sites inside and

Asterisk v1.0 is running on RH 9. I installed festival RPM (festival-1.4.2-16.i386.rpm) and edited the festival.scm file to add: (define (tts_textasterisk string mode) "(tts_textasterisk STRING MODE) Apply tts to STRING. This function is specifically designed for use in server mode so a single function call may synthesize the string. This function name may be added to the server safe

Hi, I have fitted a generalized linear mixed effects model using lmer (library lme4), and the family = quasibinomial. I have tried to obtain a MCMC sample, but on calling mcmcsamp(model1, 1000) I get the following error which I don't understand at all: Error in .local(object, n, verbose, ...) : Update not yet written traceback() delivers: 4: .Call(mer_MCMCsamp, ans, object) 3:

Hello, I am a chemical student and I make use of 'lme/lmer function' to handle experiments in split-plot structures. I know about the mcmcsamp and I think that it's very promissory. I would like knowing "the concept behind" of the mcmcsamp function. I do not want the C code of the MCMCSAMP function. I would like to get the "pseudo-algorithm" to understanding that