similar to: bootstrap: stratified resampling

If an array has missing values in different rows, plotting using the formul= a=20 interface can produce errors. Example: fake.data <- matrix(rep(-100:100, 4), ncol =3D 4) par(mfrow =3D c(1,2)) boxplot(fake.data ~ col(fake.data)) abline(h =3D 0, lty =3D 2) boxplot(as.data.frame(fake.data)) abline(h =3D 0, lty =3D 2) ##### Add the missing data fake.data[190:200, 1] <-

Dear Experts, I am trying to do a time-stratified case-crossover analysis on air pollution data and number of myocardial infarctions. In order to avoid model selection bias, I started with a simple simulation. I'm still not sure if my simulation is right. But the results I get from the "ts-case-crossover" are much more variable than those from a glm. Is this: a. Due to

Dear Experts, I am trying to do a time-stratified case-crossover analysis on air pollution data and number of myocardial infarctions. In order to avoid model selection bias, I started with a simple simulation. I'm still not sure if my simulation is right. But the results I get from the "ts-case-crossover" are much more variable than those from a glm. Is this: a. Due to the simple

Hi, You should also check my msc.features.select from caMassClass package. It has feature selection algorithm that I found useful in case of mass-spectra data. It performs individual feature selection and/or removes highly correlated neighbor features. Jarek -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] Sent: Friday, January

Dear All, I've got into the habit of installing R from the precompiled Debian binaries, including many of the packages from the r-cran-* Debian packages, and later building from source (e.g., to link against Goto's BLAS, or to build patched versions, etc). I install the newly built R to the very same place (/usr/lib/R). This allows me to build and update R when I wish, AND provides the

Dear All, This is not strictly R related (though I would implement the solution in R; besides, being this list so helpful for these kinds of stats questions...). I got a "strange" request from a colleage. He has a bunch (approx. 25000) subjects that belong to one of 12 possible classes. In addition, there are 8 covariates (factors) that can take as values either "absence"

Dear All, I found Andy Liaw's suggestion about using a NUMA (instead of SMP) kernel when running R on amd64 with > 1 CPU http://finzi.psych.upenn.edu/R/Rhelp02a/archive/35109.html A couple of questions: 1. Is this still the case with the newer dual-core opterons (e.g., the 275 et al., families) running Linux (kernel 2.6)? 2. How does this affect using Rmpi (and snow, papply, et al.)

Dear All, We are about to purchase the second edition of Agresti's "Categorical Data Analysis" (my old copy of the first ed. of that wonderful book is falling apart). I would appreciate suggestions about other comparable books which, if possible, have examples using R/S code (instead of SAS). Thanks, Ram?n -- Ram?n D?az-Uriarte Bioinformatics Unit Centro Nacional de

> x <- matrix(1:10, ncol = 2) > xc <- cor(x[, 2], x[, 0]) > cbind(xc, vector()) Process R floating point exception at Tue Feb 11 19:16:51 2003 > version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 6.2 year

Dear All, I have been using the randomForest package for a couple of difficult prediction problems (which also share p >> n). The performance is good, but since all the variables in the data set are used, interpretation of what is going on is not easy, even after looking at variable importance as produced by the randomForest run. I have tried a simple "variable selection"

Dear All, I am using the function gls (in the nlme package) and I would like to fit a heteroscedastic model, with different variances for each of the levels of two stratification variables. In p. 210 of Pinheiro & Bates ("Mixed effects models in S and S-Plus", 2000, Springer), the authors show the use of the "*" operator. However, that is not what I want, because it

Dear All, I think there is a typo in the documentation for coxph (library survival). The help says: eps: convergence threshold. Iteration will continue until the relative change in the log-likelihood is less than eps. Default is .0001. However, if I do "coxph.control()" I get: > coxph.control() $eps [1] 1e-09 So the actual eps being used is not 10-4 but

Dear All, I am using fexact.c on a C++ program I wrote. To minimize dependencies on other files (e.g., to not need to include R.h and ctest.h ---now I only include the R files Boolean.h, Constants.h, and Memory.h), I have re-written all declarations of Sints as ints and, what is potentially more serious, I have re-written the line (lines 329 and 330, in fexact.c on R-1.6.1) /* IMAX is the

(Apologies for double posting; I sent this to r-help and was suggested that I ask here which I should probable have done to begin with). *************** Dear All, I've got into the habit of installing R from the precompiled Debian binaries, including many of the packages from the r-cran-* Debian packages, and later building from source (e.g., to link against Goto's BLAS, or to build

Dear all, I have a piece of code, call it "FA", that will be called thousands of times in a typical run of function "FB". I can: a) define FA as a function outside of FB (in the global environment), and call it; b) define FA as a function inside the body of FB and call it; c) "expand inline" FA inside FB. FA mainly does data frame subsetting, runs svd's, and

Dear All, I have a list, where several components are NULL, and I'd like to obtain that very same list without the NULL components (i.e., I do not want to unlist or otherwise loose the rest of the list structure). I can do that with a loop, but how could I do it without a loop? Thanks, Ram?n -- Ram?n D?az-Uriarte Bioinformatics Unit Centro Nacional de Investigaciones Oncol?gicas (CNIO)

>Hello, I am hoping for assistance in regards to examining the contribution of stratified variables in a cox regression. A previous post by Terry Therneau noted that "That is the point of a strata; you are declaring a variable to NOT be proportional hazards, and thus there is no single "hazard ratio" that describes it". Given this purpose of stratification, in the

Hi All, I'm using R's randomForest package (and it's quite awesome!) but I'd really like to do some stratified sampling with a regression problem. However, it appears that the package was designed to only accommodate stratified sampling for classification purposes (see https://stat.ethz.ch/pipermail/r-help/2006-November/117477.html). As Andy suggests in the link just

Dear All, I've read Thomas Lumley's fortune "If the answer is parse() you should usually rethink the question.". But I am not sure it that also applies (and why) to other situations (Lumley's comment http://tolstoy.newcastle.edu.au/R/help/05/02/12204.html was in reply to accessing a list). Suppose I have similarly called functions, except for a postfix. E.g. f.1 <-

This is a follow-up to a query that was posted regarding some problems that emerge when running anova analyses for cox models, posted by Mathias Gondan: Matthias Gondan wrote: >* Dear List,*>**>* I have tried a stratified Cox Regression, it is working fine, except for*>* the "Anova"-Tests:*>**>* Here the commands (should work out of the box):*>**>*