similar to: Compiling R packages on Ubuntu

Dear All, I have just updated R to the version 2.6.2 on F8 (with the official F8 rpm). However, when running as root the following command: update.packages(checkBuilt=T) I get a bunch of errors like the ones below. Any ideas? Thanks in advance, Paul ----------------------------------------------- * Installing *source* package 'nlme' ... ** libs gcc -m32 -std=gnu99 -I/usr/include/R

Hi R-Gurus, I've been cutting along quite nicely with nlm, until I threw in the following condition in the function that nlm is minimising: if (((term*bexp) < 0.0001)) { #warning(term*bexp, "=term*bexp",psi,"=psi") theta<-2000 } Now when I run this function anywhere else, there is no problem, whether or the if's condition is met. When

HI R Gurus, > This is my first foray into using c-code with R, so ... > I had a look at the archives and did not find anything on this, so > hopefully I am not doubling up. > I have previously used the following approach where I needed some very small numbers/large (using Brobdingnag): surfacewithdiff <- function(t, y, p) { const=p["const"] kay

Hi R used with C-code experts, I had a look at the archives and did not find anything on this, so hopefully I am not doubling up. I have previously used the following approach where I needed some very small/large numbers (using Brobdingnag): surfacewithdiff <- function(t, y, p) { const=p["const"] kay =p["kay"] psii=p["psii"]

dear list, I am wondering if one can find examples and/or more detailed descriptions of modifications needed when going beyond standard corStruct classes (i.e. those already provided for use in lme/nlme)? When I looked at pages 238-239 of Pinheiro/Bates (2000): Mixed-effects models in S and S-plus, I found that I would need a bit more explicit guidance what to do for implementing a new

R Version 2.1.1 (2005-06-20); R Cocoa GUI 1.12 (1622); Mac OS X 10.4.2 (8C46) For nlme, the R package installer for CRAN (binaries) gives 3.1-60 as Repository Version as well as Installed Version. For CRAN (sources) it gives 3.1-62 as Repository Version and 3.1-60 as Installed Version. When I try to update nlme, I get * Installing *source* package 'nlme' ... ** libs gcc-3.3

Dear R-devel members, While writing a new correlation structure similar to 'corCompSymm' and intended to be used with 'gnls', I got puzzled with the 'Initialize' method. Using 'Initialize' before 'gnls' may be regarded as a mean to set an initial value for the corStruct parameter. However 'gnls' does not work properly with a

>From http://bugs.r-project.org/cgi-bin/R: If you are not sure whether you have observed a bug or not, it is a good idea to ask on the mailing list R-Help by sending an e-mail to r-help at stat.math.ethz.ch rather than submitting a bug report. I'm wondering whether to submit a bug report on this: ============================================================== >

Dear R-users, I hope you will have time to read me and I will try to be brief. I am also sorry for my poor english. I used gls function from the package nlme to correct two types of bias in my database. At first, because my replicates are spatially aggregated, I would like to fit a corStruct function like corLin, corSpher, corRatio, corExp or corGaus in my gls model, and simultaneously,

Dear R users, I fitted a repeated measure model without random effects by using lme. I will use the estimates from that model as an initial estimates to do multiple imputation for missing values of the response variable in the model. I am trying to extract the within group correlation matrix or covariance matrix. here is my code: f = lme(y ~x0+x1+trt+tim+x1:tim +tim:trt,random=~-1|subj,

Hi, I have been using the function lme() of the package nlme to model grouped data that is auto-correlated in time and in space (the data was collected on different days via a moving monitor). I am aware that I can use the correlation classes corCAR1 and corExp (among other options) to model the temporal and spatial components of the auto-correlation. However, as far as I can tell, I can only

Dear R-Users I have a problem accessing some values in the output from the summary of an lme fit. I fit the model below: ggg <- lme (ST~ -1 + as.factor(endp):Z.sas + as.factor(endp), data=dat4a, random=~-1 + as.factor(endp) + as.factor(endp):Z.sas|as.factor(trials), correlation = corSymm(form=~1|as.factor(trials)/as.factor(id)), weights=varIdent(form=~1|endp)) hh

Hi, I've got a problem that sounds a lot like this, http://r.789695.n4.nabble.com/Re-R-R-2-12-0-hangs-while-loading-RGtk2-on-FreeBSD-td3005929.html under windoze 7. but it seems to hang with this stack trace, #0? 0x77830190 in ntdll!LdrFindResource_U () ?? from /cygdrive/c/Windows/system32/ntdll.dll building goes as follows, $ ./R CMD INSTALL --no-test-load nlme_3.1-97.tar.gz *

Hello R-users, Does anyone know how to customize a corStruct object to be used in gls? I would either like to create the covariance matrix from scratch, or alter the diagonal elements of an existing corStruct object and pass that to gls. Any ideas would be appreciated!

I am trying to fit a B-spline regression model with a corStruct using gls. I am using bs() and specifying the knots myself. If I make the knots data-dependent, this works but has undesirable side-effects. I prefer to reference an auxilliary variable "knots" in my model formula. It should not be part of the data frame, as it is a vector of a different length. How can this be done? The

Good day R-Users, I have a problem accessing some values in the output from the summary of an lme fit. The structure of my data is as shown below (I have attached a copy of the full data). id trials endp Z.sas ST 1 1 -1 -1 42.42884 1 1 1 -1 48.12007 2 1 -1 -1 43.42878 2 1 1 -1

Hello R-users: I am using "yags" for fitting GEE which is giving me the same result as "Proc GENMOD". Now I have couple of questions related to yags output. (By the way, someone told me to run the geeglm for the same analysis and I did run but did not get the same result as of genmod and don't know how to correct the geeglm codes so that all three will be same!)

Dear people, A somewhat clueless question follows: I just discovered that the lme function in contrib package nlme for R, while similar to the lme function in Splus, does not use the cluster function option. This difference does not appear to be documented in the V&R `R Complements' file. I have data which is divided into 6 groups The lme model is of the form (simplified from the actual

Let's say I would like to look inside the function corBrownian in library (ape). When I type in the function name I get the following, which is not nearly the detail that goes into this function. I am wondering how to begin cracking this function open (and others) so I can learn more about it and perhaps code my own corClass one day. Thanks. > corBrownian function (value = 1, phy, form

I am trying to use nlme but instead of using one of the ?identity? variance or covariance matrixes such as compsymm or ar1. Instead I want the covariance matrix to be represented in the following manor. Is it possible to define my own covariance matrix? I have search and found papers saying I can define my own covariance matrixes and own correlation structures. Said use corstruct but not sure