similar to: Problem w/ source

Hello, I need a bit of handholding with R, specifically, with writing packages for it. I'm a systems programmer, and am, on the request of several users of our software, working on generating R interfaces. For starters, I've written the following R function (which compiles): SEXP myincr(SEXP Rinput) { // Returns input integer incremented by one int input; SEXP returner; PROTECT(Rinput =

Hallo! I have a problem with fitting data with nls. The first example with y1 (data frame df1) shows an error, the second works fine. Is there a possibility to get a fit (e.g. JMP can fit also data I can not manage to fit with R). Sometimes I also got an error singularity with starting parameters. # x-values x<-c(-1,5,8,11,13,15,16,17,18,19,21,22) # y1-values (first data set)

Hi all, Simple enough question, what kind of file is it? John van V. aka johnvv at hotmail.com ______________________________________________________ Get Your Private, Free Email at http://www.hotmail.com =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

I am embarrassed to have to ask this but can anyone tell me of a Tukey multiple comparisons procedure available for R? I have looked through the search page, through the FAQ, and in the index of V&R (1999), and I still can't find such a thing. I see there is a ptukey function and a qtukey function but that is as far as I got. Do I need to roll my own? -- Douglas Bates

Hi, does anyone out there have a recommendation for multilevel / random effects and longitudinal analysis? My dream book would be something that's both accessible to a non-statistician but rigorous (because I seem to be slowly turning into a statistician) and ideally would use R. Peter

Would it be possible to include a new command in the ${RHOME}/etc path, which updates the Library index (Rd and html) via "R LIBINDEX". I need it because I use RPM to manage three different R installations (at home, at the institute and in the seminar rooms). I put all libraries into several packages, so it is easy for me to update a single library at all these different places. But

Windows 2000 (v.5.00.2195), R 1.5.1 I have an lme object, fm0, which I examine with anova() and intervals(). The anova output indicates one of the interaction terms is significant, but the intervals output shows that the single parameter for that term includes 0.0 in its 95% CI. I believe that the anova is a conditional (sequential) test; is intervals marginal or approximate? Which should I

Hi, df <- read.table("data.txt", header=T); library(nls); fm <- nls(y ~ a*(x+d)^(-b), df, start=list(a=max(df->y,na.rm=T)/2,b=1,d=0)); I was using the following routine which was giving Singular Gradient, Error in numericDeriv(form[[3]], names(ind), env) : Missing value or an Infinity produced when evaluating the model errors. I also tried the

Dear all, Given a LME model (following the notation of Pinheiro and Bates 2000) y_i = X_i*beta + Z_i*b_i + e_i, is it possible to extract the variance-covariance matrix for the estimated beta_i hat and b_i hat from the lme fitted object? The reason for needing this is because I want to have interval prediction on the predicted values (at level = 0:1). The "predict.lme" seems to

I've noticed quite a few messages relating to large data sets bedeviling R users, and having just had to program my way through one that actually caused a "Bus error" when I tried to read it in, I'd like to ask two questions. 1) Are there any facilities for aggregation of data in R? ( I admit that this will not do much for the large data set problem immediately) 2) Is there any

I have installed the binary packages for Debian GNU/Linux release 2.3 (woody) in the U.S. mirror of the CRAN archive. They should propagate to the main CRAN archive within a day and to the other mirrors within two days. These packages have been compiled with gcc-3.0 and g77-3.0. I believe the testing distribution currently provides only a snapshot of gcc-3.0, not the latest released version, so

I have installed the binary packages for Debian GNU/Linux release 2.3 (woody) in the U.S. mirror of the CRAN archive. They should propagate to the main CRAN archive within a day and to the other mirrors within two days. These packages have been compiled with gcc-3.0 and g77-3.0. I believe the testing distribution currently provides only a snapshot of gcc-3.0, not the latest released version, so

//Referring to the response posted many years ago, copied below, what is the specific criterium used for singularity of the gradient matrix? Is a Singular Value Decomposition used to determine the singular values? Is it the gradient matrix condition number or some other criterion for determining singularity? // //Glenn // / / /> What does the error 'singular gradient' mean

Is there a recommended binary version of perl to use under Windows XP for `Rcmd build'? The R FAQ for Windows just mentions "perl". I think that Kevin Wang's document on R for Windows suggests ActiveState perl but I have not been able to install it. I am running Windows XP Professional on a laptop. The operating system was originally Windows 98 then upgraded to Windows ME

Hola, Tengo una base de datos con estructura jerárquica en la que quiero clasificar observaciones en distintas categorías. En el caso más simple, tengo una variable con dos categorías (variable Y1) y dentro de cada una de ellas hay otras dos categorías (variable Y2). Además tengo una variable explicativa cuantitativa discreta X. El banco de datos sería de este tipo: X Y1 Y2 5 0 1 9 0 0 2

Although this should be trivial, I'm having a spot of trouble. I want to make a lattice plot of the format y1+y2 ~ x | grp but then fit a lm to each y variable and add an abline of those models in different colors. If the xyplot followed y~x|grp I would write a panel function as below, but I'm unsure of how to do that with y1 and y2 without reshaping the data before hand. Thoughts

I want to create a grid of function values for use in `contour' or `persp'. The function is the log-likelihood for the gamma. The sample is stored as vector of length 20 called `Survival'. A single evaluation of the log-likelihood at, say, scale = 9 and shape = 10 would be obtained by sum(dgamma(Survival, scale = 9, shape = 10, log = TRUE)) (This may work only 0.99.0, I'm not

A newbie question: I'm trying to decide whether to run a maximum likelihood estimation in R or Stata and am wondering if the R mle routine is reasonably robust. I'm fairly certain that, with this data, in Stata I would get a lot of complaints about non-concave functions and unproductive steps attempted, but would eventually have a successful ML estimate. I believe that, with the

The goal: simulate chi square mixture distributions as a way of simulating likelihood ratio test statistics for some mixed models where the more specific model has some zero variance components (a la Pinheiro and Bates pg. 84-87) The problem: R doesn't have the function ms which is apparently used by simulate.lme In the current version of nlme for R, is there a way around this? Is it

Full_Name: W.B.Kloke Version: 1.8.0 OS: FreeBSD-4.7 Submission from: (NULL) (195.253.22.63) I found a parameter evaluation inconsistency in NLME package. I tried to use gls() inside a function, and I wanted use gls() for different subsets of a data frame: prgls <- function(name){ gls( log10(Y)~(cond-1)+(cond-1):t ,pr,subset=subject==name)} Applying this function with a string as parameter