similar to: Check errors

Sorry if this bug is fixed in the meantime, but what is this?? > m [,1] [,2] [,3] [1,] 1 2 1 [2,] 0 2 0 [3,] 1 2 1 > eigen(m) $values [1] 2 2 0 $vectors [,1] [,2] [,3] [1,] -4.194304e+06 0.7071068 -0.7071068 [2,] -4.656613e-10 0.0000000 0.0000000 [3,] -4.194304e+06 0.7071068 0.7071068 > eigen(m, symmetric=T) $values [1]

Dear list, usually, I can break a running R process with Ctrl-C. This does not seem to work if R was started from within ESS. Is there anything analogous? Thanks, Christian *********************************************************************** Christian Hennig University of Hamburg, Fachbereich Mathematik - SPST (Schwerpunkt Mathematische Statistik und Stochastische Prozesse, Zentrum fuer

Dear list, I am faced with the following model: y=E+P+M+H+PxE+Error y is a response, E and P are factors with fixed effects. M is a random effect nested in P and H is a random effect nested in M. PxE is interaction of P and E. It seems that I should fit such a model with the lme function of library nlme, but I was not able to figure out from the help page how to specify the formula. In the

Dear list, I use R 1.3.0 on Solaris. Today I realized that the html help search engine does not work at the moment (this means that I always get the search engine page again if I try to specify a search word, and click "search" or one of the prespecified topics), presumably since the latest netscape update. Do you have an idea what can be wrong? Perhaps this must be fixed not by the

Dear list, the following should fit the model log(PEPC.Wert)=fKTemp+fHerk+interaction(fKTemp,fHerk)+fMub+error, where fKTemp, fHerk are fixed effect factors and fMub is a random effects factor nested in fHerk (values are different fopr different values of fHerk). > logpepcr1 <- lme(log(PEPC.Wert) ~ fKTemp*fHerk, random= ~ 1 | fMub, na.action=na.omit) The following should be without the

Greetings RListers, I have a data set containing two types of outcomes; success and failure. Associated with each outcome are 12 different measurements. I'm trying to find out, for example, if some of the 12 measures are associated more with success or failure or, if there's any relationship at all between the measures and the outcomes (success or failure). I don't have (as yet)

Hi, this is rather a (presumed) bug report than a question because I can solve my personal statistical problem by working with hclust instead of agnes. I have done a complete linkage clustering on a dist object dm with 30 objects with agnes (R 1.8.0 on RedHat) and I want to obtain the partition that results from a cut at height=0.4. I run > cl1a <- agnes(dm, method="complete")

Hi, this is rather a (presumed) bug report than a question because I can solve my personal statistical problem by working with hclust instead of agnes. I have done a complete linkage clustering on a dist object dm with 30 objects with agnes (R 1.8.0 on RedHat) and I want to obtain the partition that results from a cut at height=0.4. I run > cl1a <- agnes(dm, method="complete")

Hi, I want R to be installed on a UNIX network (Solaris). I am not the system administrator and so I cannot do it myself. The system administrator wants to know which packages I want, and it may be a lot. Is there an easy way to download and install all packages at once? Is it a good idea? (There is a good chance that I do not need the some few packages that do not install well during such a

I'm attaching an small text file on "Getting your stuff organized in R". (Sorry if sending an attachment is not considered a correct etiquette in r-help, but this is only 7911 bytes, plain ascii text and I cannot post it in a web page at the moment). Probably all the information in this document is scattered in one or more R introduction guides, but I think that it is useful to have

Dear r-users, I am looking for an implementation of the Naive Bayes classifier for a multi-class classification problem. I can not even find the Naive Bayes classifier for two classes, though I can not believe it is not available. Can anyone help me? Uschi -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hello list, I want to apply svm from library e1071, and I want to supply class weights. I do not really understand the help entry (and there is no example) class.weights: a named vector of weights for the different classes, used for asymetric class sizes. Not all factor levels have to be supplied (default weight: 1). All components have to be named. I have two

Dear group, I would like to document more than one function on one help page using the Rd language. I tried something like \value{ \code{foo1} returns a list with components \item{arg1}{Argument 1} \item{arg2}{Argument 2} \code{foo2} returns a list with components \item{arg3}{Argument 3} \item{arg4}{Argument 4} } Unfortunately this makes the text "\code{foo2} returns a list

Hello all, So I am using the (formula entry) method for randomForests: randomForest(y~x1+x2+...+x39+x40,data=xxx,...) but the issue is that some of the items in that package dont take a formula entry - you have to explicitly state the y and x vector: randomForest(x=xxx[,c('x1','x2',...,'x40')],y=xxx[,'y'],...) Now my question is whether there is a function/way

Dear group, I want to use the mclust package on large data, and therefore I want to use a subset in the initial clustering phase. From help(mclust): k: If `k' is specified, the hierarchical clustering phase will use a sample of size `k' of the data in the initial hierarchical clustering phase. The default is to use the entire data set. m2 is a

Dear list, on p. 11 of "Writing R-extensions" I read "See the ``Guidelines for Rd-files'' for guidelines ... which should be useful..." Where can I find these guidelines? Best, Christian -- *********************************************************************** Christian Hennig Seminar fuer Statistik, ETH-Zentrum (LEO), CH-8092 Zuerich (current) and Fachbereich

Dear list, what is the fastest way to compute a multivariate mean and cov-matrix? I presume that the mean is computed in cov, so it may be a waste of time to compute the mean first and then a second time inside of cov. Is it faster to use cov.wt, which gives cov-matrix and center? And: If mean and cov should be computed on a part of the data, is it faster to use cov.wt with some weights zero, or

Hi, I want to fit a kernel density estimator by bkde of library KernSmooth. I need only the density value at the point 0. I do not understand the following behaviour: > q <- rnorm(100) > bkq <- bkde(q, bandwidth=0.11, gridsize=1, range.x=c(0,0)) Error in 0:L : NA/NaN argument > bkq <- bkde(q, bandwidth=0.11, gridsize=1, range.x=c(-1,1)) > bkq $x [1] -1 $y [1] NA > bkq

Hello list, I try to optimize some R code and it turns out that the function as.matrix takes a lot of time in my code. There is only one reason why I need as.matrix: My code should work for matrices with ncol=p and p should be allowed to be 1 or larger. Now I have a matrix x with dim(x)=(n,p), and I need to work with the submatrix y <-x[gv,], (gv a vector of n logicals) and to calculate

Dear list, here is something I do not understand about cov.rob. > dat <- rmvnorm(200,rep(0,10),diag(10)) > cov.rob(dat,method="mcd") > cov.rob(dat,method="mcd",quantile.used= floor(3*211/4)) # All fine; default for quantile.used is floor(211/2) > dat <- rmvnorm(20,rep(0,10),diag(10)) > cov.rob(dat,method="mcd") # quantile.used is floor(31/2).