similar to: New Matrix and lme4: Must reinstall lme4 if got new Matrix

Hello all, Using Ubuntu 9.04 and R 2.8.1. For a project I need to use the Zelig package, which in turn wants to use the lme4 package. When trying to use Zelig and it tries to its required packages I get the following error message. Error in dyn.load(file, DLLpath = DLLpath, ...) : function 'cholmod_start' not provided by package 'Matrix' Error in loadModelDeps(model) :

I am encountering segfaults when checking the lme4 package on an Athlon64 system if I use the acml blas. R was built as a 64-bit application using the GCC 4.0.3 compiler suite including gfortran. The version of acml is 3.5.0 gfortran64. I do not encounter the segfaults when I compile R with R's built-in BLAS. The errors occur in the first example in lme4 in a call to lmer. It looks like

Being rather inept at all things Linux, I paid a consultant to fix some things on my computer,? Unforntately, good help is hard to find.? Here's where I am: ? ... Loading required package: Matrix Loading required package: lattice Error in dyn.load(file, DLLpath = DLLpath, ...) : ? function 'cholmod_l_start' not provided by package 'Matrix' Error: package/namespace load failed

Versions 0.9975-1 of the Matrix and lme4 packages will soon be available on CRAN for use with R version 2.4.0 or later. Purpose of the packages: The Matrix package provides S4 classes and methods for sparse and dense matrices. The lme4 package provides functions for fitting and assessing linear or generalized linear mixed effects models (also called multilevel models). Like the Matrix package,

Versions 0.9975-1 of the Matrix and lme4 packages will soon be available on CRAN for use with R version 2.4.0 or later. Purpose of the packages: The Matrix package provides S4 classes and methods for sparse and dense matrices. The lme4 package provides functions for fitting and assessing linear or generalized linear mixed effects models (also called multilevel models). Like the Matrix package,

Hi there, I've been wanting to fit a GLMM and I'm not completely sure I'm doing things right. As I said in a previous message my response variable is continuous with many zeros, so I was having a hard time finding an appropriate error distribution. I read some previous help mails given to other people advising them to use the Tweedie distribution. I'm still not sure if this

Hi: I was trying to use apply on a sparse matrix from package Matrix, and I get the error: Error in asMethod(object) : Cholmod error 'problem too large' at file ../Core/cholmod_dense.c, line 106 Is there a way to apply a function to all the rows without bumping into this problem? Here is a simplified example: > dim(sm) [1] 72913 43052 > class(sm) [1] "dgCMatrix"

Hello, I have been attempting to run a poisson glmm using lme4 for some time now and have had a lot of trouble. I would say 9 times out of 10 I receive the following warning: CHOLMOD warning: %h Error in mer_finalize(ans) : Cholmod error `not positive definite' at file:../Cholesky/t_cholmod_rowfac.c, line 432 My data are counts of microbe colony forming units (CFUs) collected from

Estimado Javier Villacampa Gonzáles Si una persona se toma el trabajo de desarrollar y compartir, como es el caso de R, seguramente conoce de problemas que tuvo que decidir mientras escibía el código, y estará agradecido porque hay gente que utiliza su aporte, su trabajo no fué a la nada, todo lo contrario. En mi caso un solo autor tuvo una respuesta negativa para con migo. Javier Marcuzzi

I just (apparently) figured out how to do the stuff described in Section 5.4.2 of Writing R Extensions. I put my test toy packages on github <https://github.com/cjgeyer/linkingTo> for anyone to copy. If anyone cares to read the README and the bits of code it links to and tell me anywhere I am wrong, I would be grateful. But the main point of this e-mail is a complaint about that section

Hi, I am getting a warning message when I am fitting a generalized linear mixed model (m1.2 below). CHOLMOD warning: matrix not positive definite Error in objective(.par, ...) : Cholmod error `matrix not positive definite' at file:../Supernodal/t_cholmod_super_numeric.c, line 614 Any idea? Thanks for your help, Reza > sessionInfo() R version 2.4.1 (2006-12-18) i386-pc-mingw32

Dear all, I ran the following model without any problem previously to the update of lme4: fm2<-lmer(data=NGud,family=poisson, seed~hab*seedtray +(1|site)+(1|site:hab)) I have 25 sites, 2 habitats ("hab") per site, 8 seedtrays per habitat (4 as control, and 4 as treatment), and I'm interested in comparing the number of seed in seedtrays as a function of the treatment and its

Hola buenas. al final corri el siguiente código en mi máquina de casa. El problema es que ha habido algún cambio en la librería lme4, que hace incompatible los nuevos objetos lmer con la funcioón pamer.fnc. En este tipo de situaciones imagino que lo propio sería ponerme en contacto con el autor o intentar corregir yo mismo el código o incluso ambas. ¿Es decortes escribir al autor reportandole el

Gracias a todos por las recomendaciones. Ya me he puesto en contacto con el autor y le explicado donde esta el error. Es tan fácil como que han cambiado la estructura de los objetos tipos lmer desde la versión 2.15.3 con lo que su paquete dejo de funcionar. Por suerte la nueva estructura conserva por lo menos la parte necesaria para hacer sus funciones. Se localizar el fallo y como arreglarlo, lo

Martin and I will soon release a new version of the Matrix package with a modified API. This will affect the authors of any packages that use calls to the C function R_GetCCallable to directly access C functions in the DLL or shared object object in the libs directory of the Matrix package. (If you didn't understand that last sentence, relax - it means that you can ignore this message.) We

Hace unos meses os escribir para comunicaros que había un fallo en esta función. Como os prometí os comento la respuesta por si alguno está interesado en utilizar el paquete LMERconvenientsfucntions Dear Javier, The package has been updated and should work for you fine now. Note that function mcp.fnc does not return the fourth plot (dffits) anymore. We still have to figure out a way to compute

A new version of "the Matrix" (well, actually the R package named "Matrix") has become available on the CRAN mirrors. As some of you have noticed, the version numbers (current is version 0.999375-8) are converging to one, and we feel that we have solved enough of the many (mostly small) problems to announce that release 1.0-0 is imminent. In the DESCRIPTION of the package

A new version of "the Matrix" (well, actually the R package named "Matrix") has become available on the CRAN mirrors. As some of you have noticed, the version numbers (current is version 0.999375-8) are converging to one, and we feel that we have solved enough of the many (mostly small) problems to announce that release 1.0-0 is imminent. In the DESCRIPTION of the package

I'm sure I'm being stupid so flame away... R2.2.1 on Windoze (boohoo) latest updates of packages. I'm exploring a dataset (land) with three variables looking at an narrowly unbalanced two group (GROUP) ANCOVA of a randomised controlled trial analysing endpoint score (SFQ.LOCF.ENDPOINT) entering the baseline score (SFQ.BASELINE) as covariate and the following work fine: > res.same

Dear R-users, I'm new to R, so my apologies if this question doesn't make sense. I've tried the following model in lmer, and it works perfectly: model<-lmer(aphids~densroot+zone+(1|zone/site), family=quasipoisson) But if I try the exact same model with a different variable, totmas, the model looks as follows: model<-lmer(aphids~totmas+zone+(1|zone/site), family=quasipoisson)