similar to: methods: representation gives "unused arguments" on failure (PR#1796)

markus.jantti@iki.fi wrote: > > Full_Name: Markus Jantti > Version: 1.5.1 > OS: GNU/Linux Unstable (Sid) > Submission from: (NULL) (193.166.59.44) > > I was trying to get the package yags 3.20 by Vince Carey > <stvjc@channing.harvard.edu> > to run, but - after successfull installation -- loading the library failed with > the > message > > >

i'm trying to learn R. i have no programing experience. i tried to add on a package and just picked "yags". i can't get it to work or get any help. --- > install.packages("yags") Warning in install.packages("yags") : argument 'lib' is missing: using 'C:\Documents and Settings\j\My Documents/R/win-library/2.6' trying URL

Here is an example given from ?yags library(methods) data(stackloss) Y1 <- yags(stack.loss~Air.Flow,id=1:21, data=stackloss) How can I access parts of the output. I tried: > str(Y1) Formal class 'yagsResult' [package "yags"] with 25 slots ..@ coefficients : num [1:2] -44.13 1.02 ..@ coefnames : chr(0) > Y1$coefnames Error in Y1$coefnames : $

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!)

I have included data at the bottom of this email. It can be read in by highlighting the data and then using this command: dat <- read.table("clipboard", header = TRUE,sep="\t") I can obtain solutions with both of these: library(gee) fit.gee<-gee(score ~ chem + time, id=id, family=gaussian,corstr="exchangeable",data=dat) and library(yags) fit.yags <-

I just installed R 2.12.1, and when I went to run a few old programs with it, nothing worked. I got a ton of error messages saying such and such package was built before R 2.10.0 and needed to be reinstalled. These were not just warning messages, but error messages that prevent the programs from running when they were running just fine with R 2.10.1 For some of those packages, such as deSolve, I

I need capabilities, for my data analysis, like the Pinheiro & Bates S-Plus/R package nlme() but with binomial family and logit link. I need multiple crossed, possibly interacting fixed effects (age cohort of twin when entered study, sex of twin, sampling method used to acquire twin pair, and twin zygosity), a couple of random effects other than the cluster variable, and the ability to

Hello, Is it possible to derive Pan's QIC (2001 Biometrics 57:120) from either a fitted gee() object in the gee package or from a geese() fit in the geepack package? If so, would anyone be kind enough to provide me with code to do so? I realize that QIC is part of the output from yags() but I would like to use one of the other functions. Thanks. Richard

Hi , I use library(gee),library(geepack),library(yags) perform GEE data analysis , but all of them cannot do variable selection! Both step and stepAIC can do variable selection based on AIC criterion under linear regression and glm, but they cannot work when model is based on GEE. I want to ask whether any variable selection function or package under GEE model avaliable now? Thanks! Best,

Hi A quick question. Standard errors reported by gee/yags differs from the ones in geeglm (geepack). require(gee) require(geepack) require(yags) mm <- gee(breaks ~ tension, id=wool, data=warpbreaks, corstr="exchangeable") mm2 <- geeglm(breaks ~ tension, id=wool, data=warpbreaks, corstr="exchangeable", std.err = "san.se") mm3 <- yags(breaks ~

I have read in a file (call it myData). The actual file is about 3000x30,000 columns and object.size() says myData takes: > 737910472/(1024^2) [1] 703.7263 Unfortunately, my program ends up using 40GB as indicated by maxvmem on Unix, which causes my department's cluster to stop working. Perhaps, I have some copying going on that I cannot find. I have created an example below that mimics

Dear R users, I search the R archives and noted that the same problem has been posted but without solution. I know there IS instructions by the author of yags, but I just couldn't figured out. I know gee and geepack can also perform generalized estimating equation, but the reason why I need yags is I want to perform a Small Sample Adjustments by Michael P. Fay and Barry I. Graubard in

Dear R-ers, I am just a simple 'end-user' of R and am trying to analyse data with a binary response variable (dead or alive) in relation to weight and sex (of young birds). As some of the birds have the same biological mother, I am using mixed models with the identity of the mother as a random factor. (please, Mick Crawley, when are you going to write a chapter on mixed models with binary

Dear R-ers, I am just a simple 'end-user' of R and am trying to analyse data with a binary response variable (dead or alive) in relation to weight and sex (of young birds). As some of the birds have the same biological mother, I am using mixed models with the identity of the mother as a random factor. (please, Mick Crawley, when are you going to write a chapter on mixed models with binary

Hi, I'm using 'geepack' to run Generalized Estimating Equations. I'm aware that I can use anova to compare two models, but would it be possible to test QIC on R? It seems that there were similar questions a couple of years ago, but the question has not been answered yet. I'd appreciate if someone could show me the code! Thank you, Sachi [[alternative HTML version

Dear list: since it took me a little while to figure out how to make use of naresid, I thought that the below R code might be useful as an example on the help page. Regards, Markus # generate some data x1 <- runif(20) y <- 10 + 5*x1 + rnorm(20) summary(lm.0 <- lm(y ~ x1)) # append some NA's to y y <- c(y, rep(NA, 5)) # generate some further x1s x1 <- c(x1, runif(5)) #

Dear R-users, I intend to do a spatial analysis on the genetic structuring within a population. For this I had thought to prepare a kernel density estimate map showing the spatial distribution of individuals, while incorporating the genetic distances among individuals. I have a dataset of locations of N unique individuals (XY-coordinates) and an NxN matrix with the genetic distances given as a

Dear list: since it took me a little while to figure out how to make use of naresid, I thought that the below R code might be useful as an example on the help page. Regards, Markus # generate some data x1 <- runif(20) y <- 10 + 5*x1 + rnorm(20) summary(lm.0 <- lm(y ~ x1)) # append some NA's to y y <- c(y, rep(NA, 5)) # generate some further x1s x1 <- c(x1, runif(5)) #

I am having some trouble getting reftex, in particular the bibtex related features, to work properly in xemacs when editing text in Sweave files. I have added (defun Rnw-mode () (noweb-mode) (if (fboundp 'R-mode) (setq noweb-default-code-mode 'R-mode))) (add-to-list 'auto-mode-alist '("\\.Rnw\\'" . Rnw-mode)) (add-to-list 'auto-mode-alist

Hello Everybody: I am searching for an R package for fitting Generalized Estimating Equations (GEE) with weights (i.e. Weighted Estimating Equations). From the R documentation I found "geese(geepack)" for fitting Generalized Estimating Equations. In this documentation, under the paragraph “weights” it has been written, “an optional vector of weights to be used in the fitting process.