similar to: items in Rd file

Dear R-help, I was bitten by the behavior of all() when given logical(0): It is TRUE! (And any(logical(0)) is FALSE.) Wouldn't it be better to return logical(0) in both cases? The problem surfaced because some un-named individual called randomForest(x, y, xtest, ytest,...), and gave y as a two-level factor, but ytest as just numeric vector. I thought I check for that in my code by testing

Dear R-devel, I grabbed 1.7.0 beta from today. "make check" still fails at base-Ex.R. The last few lines of the output are: > lsf.str()#- how do the functions look like which I am using? Error in exists(nam <- nms[i], envir = envir, mode = mode) : F used instead of FALSE Execution halted Looks like the same problem as before, but at a different place. Mandrake Linux

With the same system configuration (WinNT4 SP6 and 1.7.0), I get such a Dr Watson crash each time I try to use the Change dir... command in the File menu of Rgui.exe. I doesn't seems to happen if I do this immediately after starting R but well if I already did some computation. I don't have any problem by using directly setwd(). At 12:10 23/04/03, you wrote: >Date: Tue, 22 Apr 2003

This is interesting: The crash does not happen if I run Rgui in MDI mode. The crash seemed to only occur in SDI. Andy =========================================================== For the record: Under Rgui, using the menu "File / Channge dir..." to change to a network drive crashes rgui. The crash happens if I browse to a folder on a mapped drive. I.e., if I type in

Dear R-help, Yes, I do know about the auto-loading feature. My question is more complicated than that: Suppose I loaded a package (e.g., e1071) and created an object of certain class (e.g., svm), for which there is a print method in the package to hide things that the user may not need to see (e.g., large vectors or matrices needed by methods such as predict). If the next time I started R, I

Under v1.6.2, Windows NT4 OS, when a function contains an execution error and I have placed browser() in inside the function body, the call to browser is ignored. A brief example to illustrate: > foo <- function(x) { + y <- x ^ 2 + browser() + foo2(x) ## Intentional error + x ^ 3 + } > > foo(30) Called from: foo(30) Browse[1]> Error in foo(30) : couldn't find

Christian -- You don't provide enough information (like a call) to answer this. I suspect, though, that you may be subsetting in a way that passes randomForest no data. I'm not aware offhand of an easy way to get this error from randomForest. I tried creating some data superficially similar to yours to see whether something would break if there were only a single value in the variable

Dear R-help, Can some one explain why barplot() uses changing colors in the bars by default? I should think that most of the time when people draw barplots, they want the bars to be in the same color. (At least that's what I'd expect. The first time I used barplot() in R, I was shocked to see the colors.) As an example, one example in ?layout draws a scatterplot with histograms drawn

Dear R-help, Can some one explain why barplot() uses changing colors in the bars by default? I should think that most of the time when people draw barplots, they want the bars to be in the same color. (At least that's what I'd expect. The first time I used barplot() in R, I was shocked to see the colors.) As an example, one example in ?layout draws a scatterplot with histograms drawn

A new version of the randomForest package is now available on CRAN. The DESCRIPTION is: Package: randomForest Title: Breiman's random forest for classification and regression Version: 3.4-1 Depends: R (>= 1.5.0) Author: Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener. Description: Classification and regression based on a forest of trees using

I know I should not mix base plotting functions with grid/lattice functions, but I have used a "quick-and-dirty" trick of par(new=T) in the past for annotating a trellis-drawn graph in various versions of S-PLUS. The sequence goes something like this: > windows(width = 5, height = 5, pointsize = 10) # open up the device > xyplot(y ~ x) > par(new=T) > xyplot(y2 ~ x) >

Dear R-users, While making a prediction using the randomForest function (package randomForest) I'm getting the following error message: "Error in predict.randomForest(model, newdata = CV) : No forest component in the object" Here's my complete code. For reproducing this task, please find my 2 data sets attached ( http://www.nabble.com/file/p17855119/data.rar data.rar ).

Sir, This query is related to randomForest regression using R. I have a dataset called qsar.arff which I use as my training set and then I run the following function - rf=randomForest(x=train,y=trainy,xtest=train,ytest=trainy,ntree=500) where train is a matrix of predictors without the column to be predicted(the target column), trainy is the target column.I feed the same data

The link from http://cran.r-project.org/src/contrib/PACKAGES.html#randomForest seems to be broken. To get the file try http://cran.r-project.org/src/contrib/randomForest_3.3-4.tar.gz instead. > -----Original Message----- > From: Liaw, Andy [mailto:andy_liaw at merck.com] > Sent: Thursday, September 26, 2002 8:08 PM > To: 'r-announce at stat.math.ethz.ch' > Subject:

(Sorry for the cross-post--- I wasn't sure which list is more appropriate...) Hi everyone, I've run into segfaults when using my randomForest package on large dataset (e.g., 100 x 15200) and large number of trees (e.g., ntree=7000 and mtry=3000). I'm wondering if anyone can give me some hints on where to look for the problem. The randomForest package mainly consists of two things:

(Sorry for the cross-post--- I wasn't sure which list is more appropriate...) Hi everyone, I've run into segfaults when using my randomForest package on large dataset (e.g., 100 x 15200) and large number of trees (e.g., ntree=7000 and mtry=3000). I'm wondering if anyone can give me some hints on where to look for the problem. The randomForest package mainly consists of two things:

Dear R-devel, A user reported a strange problem with predict.randomForest in the randomForest package yesterday, and I'm baffled by it. The code at the end of the message produces the error. The problem is that, in predict.randomForest, there's a .Fortran call to "runforest". One of the arguments passed in is "countts", which is a vector of doubles. The error

Hi all, Can some one tell me the difference between the following two formulas? 1. epiG.rf <-randomForest(gamma~.,data=data, na.action = na.fail,ntree = 300,xtest = NULL, ytest = NULL,replace = T, proximity =F) 2.epiG.rf <-randomForest(gamma~.,data=data, na.action = na.fail,ntree = 300,xtest = NULL, ytest = NULL,replace = T, proximity =F) [[alternative HTML version deleted]]

Hi, here are three results of random forest (version 4.0-1). The results seem to be more or less the same which is strange because I changed the classwt. I hoped that for example classwt=c(0.45,0.1,0.45) would result in fewer cases classified as class 2. Did I understand something wrong? Christian x1rf <- randomForest(x=as.data.frame(mfilters[cvtrain,]),

Dear R-devel, Can anyone give me some hints on how to go about debugging a strange segfault in my randomForest package? Here's the scoop: A user reported segfault when running predict() in the randomForest package. I asked for the data and code. The combination runs fine under WinXPPro, but does give segfault on one of our Linux boxes running R (1.7.0 through R-devel_2004-01-08) on