similar to: Matrix multiplication using Matrix package

> sessionInfo() R version 2.13.1 (2011-07-08) Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) locale: [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] Matrix_0.999375-50 lattice_0.19-30 loaded via a namespace (and not attached): [1] grid_2.13.1

Dear list, I have been working with the MatrixModels package quite a bit this week, and it is proving to be extremely valuable for my current work (I am working with several factors with many levels, leading to a sparse model matrix). However, as my knowledge of statistical theory leaves much to be desired, there are certain aspects of model evaluation etc that I am having trouble with. Has

Dear All I have a problem with the height of the boxes in the key in the following. (The text is over 2 lines to accentuate the problem of no space between the rectangles.) Is there an easy way to put a space between the rectangles; size controls the width but there appears to be nothing for the height? xyplot(1~1, key = list(corner = c(0.8,0.8),

Dear users, By running the script below, R crashes systematically at the last command, namely dev.off(), on Windows 7, but not on Windows XP. I therefore don't provide a reproducible example and do not really extract the relevant parts of the script because it has most likely nothing to do with the script itself. I can do it though if you think it might be relevant. R crashes on Windows

Dear list, I have troubles with using Bayesian logistic model with count data in bayesglm. If I consider the following artificial data set, with a response y and a covariate x, in a form of row data (a) and count (b) : a<-data.frame(y=c(rep(1,10),rep(0,6)),x=c(rep(5,6),rep(4,4),rep(5,1),rep(4,5))) a$un<-1 b<-aggregate(a$un,list(y=a$y,x=a$x),sum) names(b)[3]<-"w" A

Dear R list., I am running a script to get a compact letter display. library(lme4) library(multcomp) library(gplots) ####### Mixed Effects Model ######### data <- read.table("AJmix.txt",header=TRUE, sep="\t") attach(data) y<-cbind(positive,negative) treatment<-factor(treatment) mouse<-factor(mouse) data$obs<-1:nrow(data) names(data) detach(data) attach(data)

I've searched the help archives of both lists and apologize if I missed the answer to my question: Is there an update on developing mcmcsamp for glmer? I'm using R v. 2.7.2 (on our Unix server - will hopefully be updated soon) and 2.8.1 on my PC and get the message for both: gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),family = binomial, data = cbpp)

Hello: sort(c('A', 'b', 'C')) seems to produce different answers in R interactive than in "R CMD check", at least under both Fedora 13 and Windows 7 with Windows 7 sessionInfo() copied below: In interactive, the result is c('A', 'b', 'C'); with R CMD check, it is c('A', 'C', 'b'). This produced

The Lattice auto.key argument has a bug in R.12.2. R version 2.12.2 (2011-02-25) Platform: i386-pc-mingw32/i386 (32-bit) .... other attached packages: [1] lattice_0.19-17 loaded via a namespace (and not attached): [1] grid_2.12.2 If I set up my plot parameters as require(lattice) superpose.line.settings <- trellis.par.get("superpose.line") str(superpose.line.settings)

I am trying to read an xlsx spreadsheet (1506 rows, 501columns) all populated but getting the following error: Please advise as to how to get around this issue. > res <- read.xlsx("c:\\BSE_v2.xlsx",1) Error in .jcall("RJavaTools", "Ljava/lang/Object;", "invokeMethod", cl, : java.lang.OutOfMemoryError: Java heap space Here is the session info:

Hi, I seem to be facing a strange problem when I use Sweave for creating a LaTeX document of the R lme() output --- The EPS and PDF figure files get created, but are empty. I have attached a reproducible example below (taken from the R lme() help example). ------------------------------------------------------------------------------------ \documentclass[a4paper,10pt]{article}

Hello all I'm trying to learn how to fit a nested model in R. I found a toy example on internet where a dataset that have?3 areas and 4 sites within these areas. When I use Minitab to fit a nested model to this data, this is the ANOVA table that I got: Nested ANOVA: y versus areas, sites Analysis of Variance for y Source DF SS MS F P areas 2 4.5000 2.2500

Hi, I have been recently experimenting with the lattice package, which I must admit is just great! However, I'm sort of stuck in modifying certain parameters; Would appreciate some pointers on a couple of things: 1) Is it possible to change the font of the labels (say to computer modern) -- either in the Windows output or thru' Sweave (generating EPS/PDF)? 2) As you will notice, there

The integral of any probability density from -Inf to Inf should equal 1, correct? I don't understand last result below. > integrate(function(x) dnorm(x, 0,1), -Inf, Inf) 1 with absolute error < 9.4e-05 > integrate(function(x) dnorm(x, 100,10), -Inf, Inf) 1 with absolute error < 0.00012 > integrate(function(x) dnorm(x, 500,50), -Inf, Inf) 8.410947e-11 with absolute error <

Suppose I have the following function myFun <- function(formula, data){ f <- formula(formula) dat <- model.frame(f, data) dat } Applying it with this sample data yields a new dataframe: qqq <- data.frame(grade = c(3, NA, 3,4,5,5,4,3), score = rnorm(8), idVar = c(1:8)) dat <- myFun(score ~ grade, qqq) However, what I would like is for the resulting dataframe (dat) to include

I have not used POSIX classes previously and now have a need to use them. I have sports data with times of some athletes after different events. I need to perform some simple analyses using the times. I think I've figured out how to do this. I just want to confirm with others who have more experience that this is indeed the correct approach. If not, please suggest a more appropriate way.

Friends I'm not seeing why the following occurs: > T1 <- (A1 - A2) %*% D > T2 <- (A1 %*% D) - (A2 %*% D) > identical(T1, T2) [1] FALSE Harold > dput(A1) new("dsCMatrix" , i = c(0L, 1L, 2L, 3L, 0L, 1L, 4L, 2L, 3L, 5L) , p = c(0L, 1L, 2L, 3L, 4L, 7L, 10L) , Dim = c(6L, 6L) , Dimnames = list(NULL, NULL) , x = c(5, 5, 5, 5, 5, 5, 10, 5, 5, 10)

I've defined the following for objects of a class called jml summary.jml <- function(object, ...){ tab <- cbind(Estimate = coef(object), StdError = object$se, Infit = object$Infit, Outfit = object$Outfit) res <- list(call = object$call, coefficients = tab, N = nrow(object$Data), iter = object$Iterations) class(res) <- "summary.jml" res }

Hi folks, I'm trying to consolidate the outputs (of anova() and lrm()) from multiple runs of single-variable logistic regression. Here's how the output looks: ------------------------------------------------------------ y ~ x1 y ~ x2 y ~ x3 y ~ x4 Chi-Square 0.1342152 1.573538 1.267291 1.518200 d.f. 2 2

This evening I ran into the problem Chuck Clifton referred to in message 86 of Volume 71 Issue 9 of this list. That is, objects created by lmer change after calling pvals.fnc on that lmer object when using lme4 version 0.999375-16 and 0.999375-28. This is somewhat troublesome. The bug tracker on R-Forge (