similar to: Update Packages / help.start() (PR#4681)

Hi, How would I do this: wgetfile { "$name-$file": url => $url, file => $file, target => $target, options => $options, before => Component["md5check-$name"] } wgetfile { "$name-$md5file": url => $url, file =>

I am learning how to load C code into R-1.8.0 on Windows 98. To this end I wrote a small c program, downloaded the tools, perl, and mingw on the "building R for windows" page, and proceeded to create libR.a & libRblas.a as explained in the readme.packages. I started with a simple c program called mysum.c that can be found on:

Hello, I am new to R and I am trying to figure out how to build and install a package with nothing but R code inside. I have run 'package.skeleton' to get the basic structure. When I run 'Rcmd INSTALL testPackage' I get this error message: make: *** No rule to make target `Files/R/rw1080'. Stop. *** Installation of testPackage failed *** When I run 'Rcmd build

Hi I have tried to install some of the packages from the CRAN packages section. I am running a windows system. I did the following: (for example...) 1.downloaded the zip file (mgcv_0.9-5.tar) from http://cran.r-project.org/src/contrib/PACKAGES.html#sm 2.and saved it in the library folder of R 3.unzipped the file into the same folder 4.a folder named sm was created 5.from within

I am trying to fit the generalised linear model for the negative binomial, but the results which come out are attached below. When we fit this model using few covariates, the model converge. Does it mean that this family is fitted differently from other glm? or the number of zeros in my response variable has a limiting factor? Thanks Bruno fit <- glm.nb(pfde~SEX+...., data=data1) Warning

To whom it may concerned, I'm trying to build a new R package in a windows platform. Before that, I tried to check the previous well-know package from the CRAN using the Rcmd command. But I got the error messages as below. I think this comes from the parsing error from the Perl script in $RHOME/bin/check. In the following example, 'Program Files' is splited into 'Program',

Dear All, Can anyone please tell me where I can obtain uncompiled binary instalation files for R version 1.8. (i.e. rw1080.exe)? I can only find the uncompiled source code on CRAN today. Thank you, Mary Wisz msw@dmu.dk [[alternative HTML version deleted]]

hi, I applied coxph to my matrix of 300 samples and 215 variables and got the following error Error in fitter(X, Y, strats, offset, init, control, weights = weights, : NA/NaN/Inf in foreign function call (arg 6) In addition: Warning message: Ran out of iterations and did not converge in: fitter(X, Y, strats, offset, init, control, weights = weights, 26% of time data is censored and here

Dear all, I am reading the cch function source code. But I can not understand the following codes. Please help me. What's the fitter here? fitter <- get(method) out <- fitter(tenter = tenter, texit = texit, cc = cc, id = id, X = X, ntot = nn, robust = robust) [[alternative HTML version deleted]]

Full_Name: Gabor Grothendieck Version: 1.8.0 OS: Windows 2000 Pro Submission from: (NULL) (67.68.47.99) In R 1.8.0 on Windows 2000 suppose that \a.bat contains the following two lines: net /? dir \winnt which constitutes a simple batch file which 1. writes a help message about the built in Windows net command to stderr and 2. does a dir on the built in Windows directory WINNT writing

I gather that the pipe problem is a difficult one to solve since its highly desirable (at least for me) to be able to use Windows pipes yet its been outstanding since the previous R release. I have one idea on a possible workaround and associated feature and I wonder if this feature is feasible? I just noticed that z <- system("c:\\a.bat", intern = TRUE, invisible = TRUE) is

I tried multiple imputation with aregImpute() and fit.mult.impute() in Hmisc 3.8-3 (June 2010) and R-2.12.1. The warning message below suggests that summary(f) of fit.mult.impute() would only use the last imputed data set. Thus, the whole imputation process is ignored. "Not using a Design fitting function; summary(fit) will use standard errors, t, P from last imputation only. Use

Hi, I have a script that takes a subset of genes on a microarray and tries to fit a coxph model to the expression values for each gene. This seems to work fine but in some cases it produces warnings and/or errors. For example: Error in fitter(X, Y, strats, offset, init, control, weights = weights, : NA/NaN/Inf in foreign function call (arg 6) In addition: Warning message: In fitter(X, Y,

I have a largish dataset (1025) with around .15 of the data missing at random overall, but more like .25 in the dependent variable. I am interested in modelling the data using quantile regression, but do not know how to do this with multiply imputed data (which is what the dataset seems to need). The original plan was to use qr (or whatever) from the quantreg package as the 'fitter'

Good day R help list!!! I've been trying to do Bootstrap in R on Censored data. I encountered WARNING/ERROR messages which I could not find explanation. I've been searching on the literature for two days now and still can't find answers. I hope there's anyone out there who can help me with these two questions: 1. If the "Loglik converged before variable..." message

Hi, am very new to R and I've written an optim function, but can't get it to work least.squares.fitter<-function(start.params,gr,low.constraints,high.constraints,model.one.stepper,data,scale,ploton=F) { result<-optim(par=start.params,method=c('Nelder-Mead'),fn=least.squares.fit,lower=low.constraints,upper=high.constraints,data=data,scale=scale,ploton=ploton)

John, You can make a local version of bootcov which either: deletes these arguments from the call to fitter, or modify the switch statement to include rq.fit, the latter would need to also modify rq() to return a fitFunction component, so the first option is simpler. One of these days I'll incorporate clustered se's into summary.rq, but meanwhile this seems to be a good alternative.

While sm4.6ll<-fit.mult.impute(Surv(agesi, si)~partner+ in.love+ pubty+ FPA+ strat(gender),fitter = cph, xtrans = dated.sexrisk2.i, data = dated.sexrisk2, x=T,y=T,surv=T, time.inc=16) runs perfectly using Hmisc, Design and mice under R11 run via Sciviews-K, with library(Design) library(mice) ds2d<-datadist(dated.sexrisk2) options(datadist="ds2d")

I have a quick question, and I apologize in advance if, in asking, I expose my woeful ignorance of R and its packages. I am trying to use the bootcov function to estimate the standard errors for some regression quantiles using a cluster bootstrap. However, it seems that bootcov passes arguments that rq.fit doesn't like, preventing the command from executing. Here is an example:

I just found a bug in fisher.test(). This is rw1080, on windows XP. A p-value can certainly not be Inf, but: > religion Costumbres rel orig Religion Si Algunas veces Nunca católica 2121 4700 6234 prot/evan 100 216 2461 otra C 27 67 502 otra 0 0 14 > fisher.test(religion, workspace=2000000)