similar to: Problems in installing MCMCglmm package

Hi folks, When I try to load package 'lme4' on my Linux box (64-bit Ubuntu 9.04), I get the following error: ------------------------------------- > library(lme4) Error in dyn.load(file, DLLpath = DLLpath, ...) : function 'cholmod_start' not provided by package 'Matrix' Error: package/namespace load failed for 'lme4' ------------------------------------ I

Hi List, I have a problem with using Latex and Sweave for creating a document. So I downloaded the Sweave manual from http://www.statistik.lmu.de/~leisch/Sweave/Sweave-manual.pdf and i have tried to replicate the example on pages 4-5, but i encounter the following problem: IT DOES NOT WORK. I can run Sweave, create the .tex file and then when building the .tex file in TeXnikCenter i get all

Dear All, to my surprise as.factor does not accept a levels argument. Maybe I did not read the documentation well enough. See the example below. I wanted to use ch1 as factor in the newdata argument of survfit, so I assumed that I could write as.factor(ch1, levels=ch1), since the order should be kept. But as.factor(ch1, levels=ch1) results in the error: Error in as.factor(ch1, levels = ch1)

Hi, I am writing an Sweave document and am using 'xtable' to make frequency tables of diagnoses of people undergoing cholecystectomy. Some of these diagnoses contain Danish characters ("?", "?", and "?"), and these characters are all garbled in the Latex document after I run Sweave. The odd thing is, everything looks absolutely right in the R console, and if

Hi, I don't understand the following. When I create a small artificial set of date information in class POSIXct, I can calculate the mean and the median: a = as.POSIXct(Sys.time()) a = a + 60*0:10; a [1] "2009-03-10 11:30:16 EDT" "2009-03-10 11:31:16 EDT" "2009-03-10 11:32:16 EDT" [4] "2009-03-10 11:33:16 EDT" "2009-03-10 11:34:16

Dear all, I had trouble in setting up WinBUGS on my Mac, and I'm seeking for some help here. I followed the instruction by Tom Palmer here: http://www.ruudwetzels.com/MacBUGS/winbugsonmacosx.pdf I installed Darwine 1.1.21, and downloaded WinBUGS14. However, when I double-clicked the WinBUGS14.exe file, a black-box dialog window poped up, and I got error message in the Wine log as

Hi All, The data set that I have is a cluster data, and I want to run a HLM mixed model with multi-level response. Here is my data set: response: - Level (num: 1, 2, 3, 4, 5 - 5 levels) Covariates: - Type (Factor: A, B, C - 3 levels) - yr (num: 2006, 2007, ...) - Male (num: 0=not Male, 1=Male - 2 levels) - Ethnicity (Factor: A, B, H, ..., - 7 levels) - ELL (num: 0, 1, - 2

> On Mar 22, 2018, at 1:31 PM, Michelle Kline <michelle.ann.kline at gmail.com> wrote: > > Hi, > > Thanks in advance for any help on this question. I'm running multinomial > models using the MCMCglmm package. The models have 5 outcome variables > (each with count data), and an additional two random effects built into the > models. The issue is that when I use

Hi, Thanks in advance for any help on this question. I'm running multinomial models using the MCMCglmm package. The models have 5 outcome variables (each with count data), and an additional two random effects built into the models. The issue is that when I use the following code, the summary only gives me results for four of the outcome variables. Here is the code for my model: m3.random

Dear R-users, I would like to fit a glmm with cross-classified random effects with the function MCMCglmm. Something along the lines: model1<-MCMCglmm(response~pred1, random=~re1+re2, data=data) where re1 and re2 should be crossed random effects. I was wondering whether you could tell me specifying cross-classified random effects in MCMCglmm requires a particular syntax? Are there any

Hi David, Thanks for your comment. I haven't posted the data because they are unpublished and include human subjects so there are issues with sharing on a list serv, but I thought perhaps someone had encountered a similar problem and would already know the answer. I will reconsider whether my University's ethics approval would allow me to post the data and update the question if I think

Dear all, I would like to add mixed effects in a multinomial model and I am trying to use MCMCglmm for that. The main problem I face: my data set consits of a trapping data set, where the observation at eah trap (1 or 0 for each species) have been aggregated per traplines. Therefore we have a proportion of presence/absence for each species per trapline. ex: ID_line mesh habitat Apsy Mygl

Hi R-users: Can anyone give an example of giving starting values for MCMCglmm? I can't find any anywhere. I have 1 random effect (physicians, and there are 50 of them) and family="ordinal"? How can I specify starting values for my fixed effects? It doesn't seem to have the option to do so. Thanks, Ping

Dear list-member, I am currently developing a package with S4 classes. The NAMESPACE and DESCRIPTION is printed below. Within this package I have set a method "residuals" for two classes. In version 2.8.1 these two are reported whereas in R-Devel (2009-01-28 r47766). What have I missed? What has changed and how can I rectify the issue? Your help and pointers are welcome. For 2.8.1:

Thanks for your answers Stephen and Ben, I hope I am posting on the correct list now. I managed so far to run the multinomial model with random effect with the following command: MCMCglmm(fixed=cbind(Apsy,Mygl,Crle,Crru,Miag,empty) ~ habitat:trait,random=~idh(trait):mesh,family="multinomial12", data=dataA,rcov=~trait:units) (where multiple responses are different species, Habitat

Hi all, I previously emailed about a multinomial model, and after seeking some additional help, realized that since my response/outcome variables are not mutually exclusive, I need to use a multi-response model that is *not* multinomial. I'm now trying to figure out how to specify the priors on the multi-response model. Any help would be much appreciated. My data look like this: X

Dear R users, I?d like to pose aquestion about pMCMC and HDP. I have performed a mixed logistic regression by MCMCglmm (a very good package) obtaining the following results: Iterations = 250001:799901 Thinning interval = 100 Sample size = 5500 DIC: 10.17416 G-structure: ~ID_an post.mean l-95% CI u-95% CIeff.samp ID_an 0.7023 0.0001367 3.678 2126 R-structure: ~units post.mean l-95%

1. (Mainly) Statistical issues are generally off topic on this list. You might want to try the r-sig-mixed-models list instead. 2. However, I think a better answer is to seek local statistical expertise in order to have an extended discussion about your research intent in order to avoid producing yet more irreproducible psychological research. Cheers, Bert Bert Gunter "The trouble with

Hi, I have a dataset where the residual variance decreases with on one of the predictors (population size). Currently, the full model looks like this: prior<-list(R=list(V=1e-16, nu=-2),G1=list(V=diag(2), nu=2)) m<-MCMCglmm(response~poly(population size,2)*poly(other predictor,2)+time, random=~us(1+time):population, data=data, prior=prior) Basically, it's a random regression with

Hello, In package survival should be a dataset bladder1. http://stat.ethz.ch/R-manual/R-devel/library/survival/html/bladder.html I can not open it (not found). Both bladder and bladder2 are there. Thanks, Petra