similar to: spatial corStruct in lme

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

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

Hello, I would like to fit correlation structures with nlme, but R crashes. My data is similar to the "growth of orange trees" example from Pinheiro and Bates (2000), but data are not equally spaced in time, as the last observation is taken after 6 days ( and not 2 as the others). This is the code I'm using: library(nlme)

I am having trouble fitting correlation structures within nlme. I would like to fit corCAR1, corGaus and corExp correlation structures to my data. I either get the error "step halving reduced below minimum in pnls step" or alternatively R crashes. My dataset is similar to the CO2 example in the nlme package. The one major difference is that in my case the 'conc' steps are

Hello folks, I have some data where spatial autocorrelation seems to be a serious problem, and I'm unclear on how to deal with it in R. I've tried to do my homework - read through 'The R Book,' use the online help in R, search the internet, etc. - and I still have some unanswered questions. I'd greatly appreciate any help you could offer. The super-super short explanation is

I have spatial data on a sphere (the Earth) for which I would like to run an gls model assuming that the errors are autcorrelated, i.e. including a corSpatial correlation in the model specification. In this case the distance metric should be calculated on the sphere, therefore metric = "euclidean" in (for example) corSpher would be incorrect. I would be grateful for help on how to

I'm looking for something in R to fit a multivariate linear model robustly, using an M-estimator or any of the myriad of other robust methods for linear models implemented in robustbase or methods based on MCD or MVE covariance estimation (package rrcov). E.g., one can fit an mlm for the iris data as: iris.mod <- lm(cbind(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) ~ Species,

Hello R gurus, I want to calculate the Spearman rho between two ranked lists. I am getting results with cor.test that differ in comparison to my own spearman function: > my.spearman function(l1, l2) { if(length(l1) != length(l2)) stop("lists must have same length") r1 <- rank(l1) r2 <- rank(l2) dsq <- sapply(r1-r2,function(x) x^2) 1 - ((6 * sum(dsq))

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

I am unable to compile R packages from source on Ubuntu dapper/edgy. Does anybody have an experience? When I do install.packages("nlme",depend=TRUE), I get following error messages. Can someone help? I get similar messages for any package I try to compile. VR ------------- * Installing *source* package 'nlme' ... ** libs gcc -I/usr/share/R/include -I/usr/share/R/include

I'm using the WINDOWS 95 version of R (with midified menu "exe.zip"): I tried to do library(mva) data(quakes) quakes<-quakes[sample(seq(1:1000),100),1:5] cmd.dsq<-cmdscale(dsq) Error in .C("dblcen", x, as.integer(n)) : C/Fortran function not in load table how can I solve this problem? -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

I'm using rseptbeta for w95, I tried to do: library(mva) data(quakes) quakes<-quakes[sample(seq(1:1000),100),1:5] cmd.dsq<-cmdscale(dsq) Error in .C("dblcen", x, as.integer(n)) : C/Fortran function not in load table how can I solve this problem? Andrea Rossetti _______________________________________________________ Statistica & Informatica per la Gestione delle Imprese

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

>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 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

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

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 am stuck in a looping problem. It might be an easy problem for experienced R users but I have been unable to do it. Any kind of help or advice will be great appreciated. I am creating a spatial grid and have a list of spatial points in a folder. I can read the spatial points separately and get a count of the points in the spatial grid in R. The output should be a table showing the counts of

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 *