similar to: Problem with the 'hist' function

installed from the binary image (http://cran.r-project.org/bin/ macosx/) on an intel mac 10.4.10 throws three warnings: ----------------- R version 2.5.1 (2007-06-27) Copyright (C) 2007 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or

hello, I am using LDA and QDA function of MASS library. I understand Fisher LDA is a method non-probabilistic in nature, so I wonder what happens when I try to predict my test set examples as in: > fit <- lda(labels~., data=train.table, prior=c(.5,.5)) > pred <- predict(fit, data=test.table, prior=c(.5,.5)) Specifically I ask this because in my problem there are 700 examples

> hi all, > I am using optim. I am getting the following error message: > > Error in optim(par = start.vals[, h], fn = post.func.pois, gr = post.grad. > pois, : > L-BFGS-B needs finite values of fn > > If I look at optim typing '> optim' it seems that the error comes from > inside .Internal(optim), so I wonder how can I see the code for .Internal(

Hello all, I am using libraries (mva,cluster) to produce dendrograms. With 1000 examples the dendrogram gets too crowded, and i am wondering whether there is an option (which i cannot find) to set the number of leaf nodes, like in matlab, and return the plot and the assignment map examples -> leaf nodes. Any suggestion is appreciated. Thanks Edo

hello all, I am trying to print a ps file as part of a function as in: func <- function (..., filename="temp.ps") { # some stuff [...] # plot eval( cat("postscript(\"",filename,"\")\n", sep="") ) plot(...) abline(...) dev.off() # more stuff [...] } but it does not work. Nor it does with 'paste' instead

hi there, i have one more question about LDA. just to make surei understand, suppose we have two classes, then if i specify a prior=c(.3,.7) in lda(...) this will affect my between classes covariance matrix as in: SB = (.3*m1 - .7*m2) %*% inv(Sigma) %*% t(.3*m1 - .7*m2) [is Sigma affected ?] and the threshold to decide which class to assign 'test' data = log(.3/.7) if i specify a

Hi, I am out of town and will get back to you on the 13th of July. Leo >>> "r-help at stat.math.ethz.ch" 06/27/03 00:32 >>> Send R-help mailing list submissions to r-help at stat.math.ethz.ch To subscribe or unsubscribe via the World Wide Web, visit https://www.stat.math.ethz.ch/mailman/listinfo/r-help or, via email, send a message with subject or body

hi all, I am fitting a logistic regression model on binary data. I care about the fitted probabilities, so I am not worried about infinite (or non-existent) MLEs. I use: > glm(Y~., data=X, weights=wgt, family=binomial(link=logit), maxit=250) I understand the three ways to fit model, and in my case Y is a factor, one column > Y <- c(rep("A",679), rep("B",38))

Greetings, I'm having a really hard time getting this to work the way I want it to. I have a Samba file server (3.0.25b-2) on Fedora 7 which serves around 20 clients (mostly WinXP but a couple of Macs). They all login via a single shared samba user which has full read/write permissions for the entire served directory. Unfortunately, I have two major problems: 1.) On an XP client, when

hi all, I am fitting a logistic regression model on binary data. I care about the fitted probabilities, so I am not worried about infinite (or non-existent) MLEs. I use: > glm(Y~., data=X, weights=wgt, family=binomial(link=logit), maxit=250) I understand the three ways to fit model, and in my case Y is a factor, one column > Y <- c(rep("A",679), rep("B",38))