similar to: Warning in 'probtrans'-function ('mstate'-package)

hello,everyone: I am now confused in multistate survival , when I want to poccess a multistate survival analysis, I turn to R and the package 'mstate' and packege 'cmprsk'. When I come to publishing the article. Follow requirement of the magzine, the statistic is carry out in LTA package (which was said to be a authority in intauterine from WHO) . There we found difference

I am about to write a "cluster-lite" R solution for myself. I wanted to know whether it already exists. If not, I will probably write up how I do this, and I will make the code available. Background: we have various linux and OSX systems, which are networked, but not set up as a cluster. I have no one here to set up a cluster, so I need a "hack" that facilitates parallel

Hi, I'm trying the brlr function in a penalized logistic regression function. However, I am not sure why I am encountering errors. I hope to seek your advice here. (output below) Thank you! Your help is truly appreciated. Min-Han #No error here, the glm seems to work fine >

It might be a bit faster to do matrix indexing: R> tbm <- as.matrix(tb) # turn it into a character matrix R> tmat[cbind(match(tbm[,2], rownames(tmat)), match(tbm[,1], colnames(tmat)))] <- 1 > tmat Apple Orange Mango Grape Star A 1 1 1 0 0 O 1 1 0 0 0 M 0 0 1 0 0 G 0 0 0 0 0 S 1 1 1 0

Greetings, My goal is to create a Markov transition matrix (probability of moving from one state to another) with the 'highest traffic' portion of the matrix occupying the top-left section. Consider the following sample: inputData <- c( c(5, 3, 1, 6, 7), c(9, 7, 3, 10, 11), c(1, 2, 3, 4, 5), c(2, 4, 6, 8, 10), c(9, 5, 2, 1, 1) ) MAT <- matrix(inputData,

Dear WizaRds, My goal is to program the VS-KM algorithm by Brusco and Cradit 01 and I have come to a complete stop in my efforts. Maybe anybody is willing to follow my thoughts and offer some help. In a first step, I want to use a single variable for the partitioning process. As the center-matrix I use the objects that belong to the cluster I found with the hierarchial Ward algorithm. Then,

Thank you for your replies so far. Sorry for bothering you again, but I'm still not able to get what I need as I don't understand all parts of the replies (just using R for easy things....). Is there a code for plane3d() like some of you sent me for points3d()? I was not able to get that out of the scatterplot3d package... What I can do is to get the x,y and z-range for the xlim,ylim and

hi: I have matrix with dimensions(200 X 20,000). I have another file, a tab-delim file where first column variables are row names and second column variables are column names. For instance: > tmat Apple Orange Mango Grape Star A 0 0 0 0 0 O 0 0 0 0 0 M 0 0 0 0 0 G 0 0 0 0 0 S 0 0 0 0 0

Hello all, I was going to solve (n-m)! * (n-k)! = 0.5 *n! * (n-m-k)! for m when values of n and k are provided n1<-c(10,13,18,30,60,100,500)         # values of n kx<-seq(1,7,1);                               # values of k slv2<-lapply(n1,function(n){    slv1<-lapply(kx,function(k){              lhs<-function(m)              {                

I have written a bash script (see below) to generate bootable SD-USB images using syslinux as booter. The script works OK with versions 3.63 and 3.71, but I get a null pointer error executing /tmp/$SYSLINUX/linux/syslinux -sf -o 16384 SD.img in 3.72. If you execute $ sudo sh SDformat.sh sys then you can test the image easily with qemu $ qemu -hda SD.img ++++++ SDformat.sh

Dear WizaRds, although this might be a trivial question to the community, I was unable to find anything solving my problem in the help files on CRAN. Please help. Suppose I have 4 variables and want to use all possible combinations: 1,2 1,3 1,4 2,3 2,4 3,4 for a further kmeans partitioning. I tried permutations() of package e1071, but this is not what I need. Thank you for your help and

Dear all, I am using R 2.9.2 on Windows XP. I am undertaking a simulation study to consider methods of external validation in the context of missing covariates in the validation data set. I would like to use Royston's measure of prognostic separation as a method of external validation. Although there is no R code for this, the author informs me that it should be easy: 1. Calculate the

Dear Sir/Ma, I Adelabu.A.A, one of the R-users from Nigeria. When am running a coxph command the below error was generated, and have try some idea but not going through. kindly please assist: > cox1 <- coxph(Surv(tmonth,status) ~ sex + age + marital + sumassure, X) Warning message: In fitter(X, Y, strats, offset, init, control, weights = weights, : Ran out of iterations and did not

I have posted an update to the GAM package. Note that this package implements gam() as described in the "White" S book (Statistical models in S). In particular, you can fit models with lo() terms (local regression) and/or s() terms (smoothing splines), mixed in, of course, with any terms appropriate for glms. A number of bugs in version 0.92 have been fixed; notably 1) some problems

I have posted an update to the GAM package. Note that this package implements gam() as described in the "White" S book (Statistical models in S). In particular, you can fit models with lo() terms (local regression) and/or s() terms (smoothing splines), mixed in, of course, with any terms appropriate for glms. A number of bugs in version 0.92 have been fixed; notably 1) some problems

The model.frame function has trouble with a certain type of really long formula. Here is a test: tname <- paste('var', 1:50, sep='') tmat <- matrix(rnorm(500), ncol=50, dimnames=list(NULL, tname)) tdata <- data.frame(tmat) temp1 <- paste( paste(tname, tname, sep='='), collapse=', ') temp2 <- paste("~1 + cbind(", temp1, ")")

Since the number of choices is small (6), how about this? Starting with Jeff's initial DFM: DFM <- structure(list(obs = 1:6, start = structure(c(16467, 14710, 13152, 13787, 15126, 12696), class = "Date"), end = structure(c(17167, 14975, 13636, 13879, 15340, 12753), class = "Date"), D = c(700, 265, 484, 92, 214, 57), bin = structure(c(6L, 3L, 5L, 1L, 3L, 1L), .Label

Dear R-devel list members, Ben Fairbank draw it to my attention that factanal() (in the stats package) doesn't report factor correlations for oblique rotations. Looking at the source, I see that factanal also doesn't save the factor-transformation (rotation) matrix from which these correlations can be computed. I've modified the source, attached below, so that the transformation

Hi All, I have a Data.frame that looks like that one below. I would like to do some text mining on it to possibly find some patterns between Opis, ACklasifikacija and Vodja. I looked over a tm package which loks promissing, more specifically DocumentTermMatrix or TermDocumentMatrix. But I can not figure out how to change my data from data.frame to Corpus or VCorpus. Globina

Full_Name: Laurent Gautier Version: 1.3.0-patched OS: IRIX 6.5 Submission from: (NULL) (130.225.67.199) Hello, The function La.eigen, called by cmdscale in the package mva behaves an unexplicable way (for me). The following lines show what happened. I tried the very same on linux, and it worked fine. >a <- matrix(c(1,2,3,2),3,3) >a [,1] [,2] [,3] [1,] 1 2 3 [2,]