similar to: Adding locfit confidence intervals in trelis xyplot

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

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 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 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)

Hi, I'm running a tutorial ("Meta-analyses of data from two (or more) microarray data sets"), which use wgcna package. I have an error in the function modulePreservation (it is below). I'm using R2.13 Can you help me? Do you know, what is happens? Thanks Raquel multiExpr = list(A = list(data=t(badea)),B = list(data=t(mayo))) # two independent datasets (dim = 13447 x 36) mp =

> 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 R users, I have changed my R version to the new 1.8.1 and some problems appears when using the previous levelplot code. This is a simple example: a <-1:10 b <-11:20 j <- rnorm(100) grid<-expand.grid(a = a, b = b) levelplot(j~a*b, grid) Normaly in my previous vs this was suffice to produce the levelplot. Now, an empty R graphics device appears with the following error

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, 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, Under Debian GNU/Linux La.svd (with method = "dgesdd") sometimes gives the error "Error in La.svd(data, nu = 0, nv = min(nrow, ncol), method = "dgesdd") : LAPACK routine DGESDD gave error code -12" It seems not to depend on the data per se, but on the relationship between numbers of rows and columns. For example, if the number of columns is 100,

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 <-

Hi all, I would like to do some QSAR analysis (quantitative structure activity relationship). I need to use some Partial Least Squares (PLS) regression, but I have not seen this option on the R-project. Is it possible to do this kind of regression on R? thank you in advance best regards, olivier [[alternate HTML version deleted]]

Dear list members, I am trying to understand this output from the smoothing package locfit (1.5-4, running on R 2.8.1 on Windows Vista 64 bit). # sample code x<-1:100 y<-rnorm(100) fit<-locfit(y~x,family="gaussian") #default parameters are fine plot(fit,band="global") #plot seems "reasonable", confidence bands use a global estimate of variance

I'm using the package 'locfit' for nonparametric regression. This package contains the function 'scb' to compute simultaneous confidence bands. The variance of the data is unknown. Up to now I compute a fit with 'locfit'. Afterwards an estimate of the residual variance is computed by the function 'rv'. The weights in the 'scb'-function are set 1/sigma^2

Dear All, I was writing a small wrapper to bootstrap a classification algorithm, but if we generate the indices in the "usual way" as: bootindex <- sample(index, N, replace = TRUE) there is a non-zero probability that all the samples belong to only one class, thus leading to problems in the fitting (or that some classes will end up with only one sample, which will be a problem

Hi All, Sorry if this is a repost (a quick browse didn't give me the answer). I wonder if there are packages that can do the feature selection and classification at the same time. For instance, I am using SVM to classify my samples, but it's easy to get overfitted if using all of the features. Thus, it is necessary to select "good" features to build an optimum hyperplane (?).

Ich habe in R eine Version von SIR gefunden und ausprobiert. Leider kann diese multivariate Responses nicht verarbeiten. Gibt es in R eine ausgefeilte Version von SIR?

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

To avoid angry replies, let me first say that I know that the use of Type III sums of squares is controversial, and that some statisticians recommend instead that significance be judged using the non-marginal terms in the ANOVA. However, given that type III SS is also demanded by some… is there a function (equivalent to drop1 for lm) to obtain type III sums of squares for mixed models using the