similar to: Problem of lmer under FreeBSD

Dear all I want to compute Monte Carlo p-values in lmer-models based on sampled data sets. To speed up calculations, I've tried to use internal functions from the Matrix package (as suggested ealier on the list by Doug Bates). So I did: fm2 <- lmer(resistance ~ ET + position + (1|Grp), Semiconductor,method='ML') simdata<-simulate(fm2,nsim=1) ynew <- simdata[,1] mer

Dears Sirs During my computational work I encountered unexpected behaviour when calling "ar" function. I want to select the order p of the autoregressive approximation by AIC criterion and sometimes an error occurs. Example: # time series

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation

Dear Dr. Bates, and R-help, I've tried the anova function to test the difference between two coefficients, as shown on page 225 of your book "Mixed Effects Models in S and S-Plus (Statistics and Computing)". When I type: anova( fm2BW.lme, L = c(TimeDiet2 = 1, TimeDiet3 = -1) ) I got the following error message: Error: unexpected '=' in "anova( fm2BW.lme, L =

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, I get the following error message when trying to use the display function on the ARM package: > display(model) Error in .Internal(round(x, digits)) : no internal function "round" Looks like some kind of mismatch between the ARM package and some others? Can I somehow get around it? I have learned to like the display function to print model summaries. Here is my sessionInfo():

Hi, I am trying to find a way to automate production of page numbers in plots produced using the lattice package. To do this, I started playing around with setHook which works fine with vanilla plot, but the hook 'plot.new' doesn't appear to be relevant to the lattice package. I was wondering if there is a alternative someone can suggest for use with the lattice package. Example

Hi all, I am encountering a strange issue with the Matrix package. I have just built R-devel from source on my macbook pro, and I wonder if others can reproduce this problem. I will give example code to go along: Starting a fresh R session: R version 2.6.0 Under development (unstable) (2007-08-30 r42697) Copyright (C) 2007 The R Foundation for Statistical Computing ISBN 3-900051-07-0 ... >

Hi folks - After upgrading to the latest version of Rmetrics, I can't read in data like I used to. Is anyone seeing the following? It seems to truncate the dates after I use "as.timeSeries". -John SP500<-read.table("SP500.csv",header=TRUE,sep=",") > head(SP500) Date Open High Low Close Volume 1 08/04/06 1280.26 1292.92

Dear All, I?m using lme to analyze a time series gene expression data. I don?t have all animals in all times, the number of animals in each time is different and I have lots of NA values. An example file can be downloaded at lbmp.fcav.unesp.br/leonardo and the code used is the following: teste<-read.table(file='example.csv',sep=',',header=T) B<-1366 library(nlme)

I am not sure whether there is a bug. When I tested the example given for "glht" in the help, I entered the following error: Running commands: amod <- aov(minutes ~ blanket, data = recovery) rht <- glht(amod, linfct = mcp(blanket = "Dunnett"), alternative = "less") Errors are: Error in try(coef.(model)) : could not find function

Hi all, I've now got a problem with some modified lmer code (function lmer1 pasted at end) - I've made only three changes to the lmer code (marked), and I'm not really looking for comments on this function, but would like to know why execution of the following commands that use it almost invariably (but not quite predictably) leads to the R session terminating. Here's the command

Hi all, I compiled 64-bit R on an Apple Mac G5 running OS X, but it failed make check. Simon Urbanek suggested I post results to R-devel. > On Nov 6, 2007, at 10:23 PM, Steven McKinney wrote: > > > Hi Simon, > > > > Would you be able to give more guidance on how to compile 64-bit > > libiconv for Tiger, > > You can get the sources from Apple and compile

On starting an R session, I get the messages: Fatal errir: unable to restore save data in .RData Error in fun(...): couldn't find function "assignInNamespace" Error: .onLoad failed in 'loadNamespace' for 'Matrix' The only object in my .RData is last.warning, thus: > last.warning $"optim or nlminb returned message false convergence (8)"

Dear Srinidhi, You are trying to fit 1 random intercept and 2 random slopes per individual, while you have at most 3 observations per individual. You simply don't have enough data to fit the random slopes. Reduce the random part to (1|ID). Best regards, Thierry ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK

Dear Srinidhi, You are trying to fit 1 random intercept and 2 random slopes per individual, while you have at most 3 observations per individual. You simply don't have enough data to fit the random slopes. Reduce the random part to (1|ID). Best regards, Thierry ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK

Hi, I was taken off guard by the following behavior in a lattice plot. I frequently want to add a predicted curve defined at more points than in the formula expression of xyplot. There have been numerous examples of how to do this on r-help, but I still often struggle to make this work. I just realized that specifying one of the axes on a log scale does not guarantee that the added data for a

is it possible to pass parameters from a .cfg file to the newly booted kernel? my setup is pxelinux where the relevent config is label fbsd63 kernel memdisk append initrd=/freebsd6.3.hd harddisk what i would like to do is pass in some parameter so the booted kernel can behave differently. i've looked in teh archives without success, although i did see an elliptic reference to

Dear list I try to run a bootstrap with lmer. I often, but not always, get the error message: Error in objective(.par, ...) : Leading minor of order 6 in downdated X'X is not positive definite (with the number (here 6) varying) In R-archives I came across some threads that treated this problem, nevertheless they refer to lmer when using it with family = "binomial", so the