similar to: New Package: ipred - Improved predictors

Hi, yesterday I installed the current R-devel and now I get the following warning message for program codes which made no problems under version R-1.2.3: Example: R> read.table("test.dat") Warning message: incomplete final line in: readLines(con, n, ok) where `test.dat' looks like peters at artemis:~ > cat test.dat 1 2 3peters at artemis:~ > i.e. without a newline

Some time ago I came across the function object.size() to estimate the size of an R object. I don't know if the behavior of the function is intended to be quite "user unfriendly" as it is right now or if just nobody was thinking/caring about it. I have two suggestions to improve it: - Why is it named object.size() and not just size()? The latter would be far more intuitive and

Hi, the following example aiming at a class containing a logical slot segfaults under R-1.9.0 when `gctorture(on = TRUE)' is used: Code code (dummy.c): #include <Rdefines.h> SEXP foo() { SEXP ans; PROTECT(ans = NEW_OBJECT(MAKE_CLASS("test"))); SET_SLOT(ans, install("lgl"), allocVector(LGLSXP, 1)); LOGICAL(GET_SLOT(ans,

I just realized that in the call to `csimint' the argument `asympt=TRUE' is missing since we need to compute the confidence intervals for a glm based on the normal approximation. Torsten --------------------------------------------------------------------- library(multcomp) set.seed(290875) # a factor at three levels group <- factor(c(rep(1,10), rep(2, 10), rep(3,10))) # Williams

Dear List, I have a question regarding "ipred" package. Under 10-fold cv, for different knn ( = 1,3,...25), I am getting same misclassification errors: ############################################# library(ipred) data(iris) cv.k = 10 ## 10-fold cross-validation bwpredict.knn <- function(object, newdata) predict.ipredknn(object, newdata, type="class") for (i in

Dear R users, I have been using the rpart procedure to predict the occurrence of depression in a large data file. Since the prevalence is very low (5%), I have been using classification trees with a loss matrix that penalized false negatives more than false positives. I have become interesested in bagging these (successful!) classification trees, and have been using the ipred package for

Dear useRs, we are happy to announce the release of mboost 2.0-0 on CRAN: http://cran.r-project.org/package=mboost This version contains major updates and changes to the implementation of the main algorithm. Some slight changes to the user-interface where necessary. Please consult the manual and the list of CHANGES below. The package 'mboost' (Model-based Boosting) implements

Dear useRs, we are happy to announce the release of mboost 2.0-0 on CRAN: http://cran.r-project.org/package=mboost This version contains major updates and changes to the implementation of the main algorithm. Some slight changes to the user-interface where necessary. Please consult the manual and the list of CHANGES below. The package 'mboost' (Model-based Boosting) implements

I wanted to report this issue here so others may not find themselves alone and as the author is apparently active on the list. I havent done an exhaustive test by any means, cause I dont have time. But here's a small example. Apparently the "ns" argument is the one that is killing it. I've gotten several different segfault messages, the only other one I remember said "out

Hello! I'm Taeho, a graduate student in South Korea. In order to get .632+ bootstrap error using random forest, I have tried to use 'ipred' package; more specifically the function 'errorest' has been used. Following the guidelines, I made a simple command line like below: error<-errorest(class ~ ., data=data, model=randomForest, estimator = "632plus")$err

Hi, I'm trying to find information about rsurv "Simulating Survival data" in the IPred package, without luck this far. In the description of this function we are asked to consult Hothorn et al. (2003) for the details. This paper is not in the reference list. Should it be same authors (2004)? In that case I will try my library, in any other case could someone please give me

Dear all, Does anybody can explain this: different results got when all the same parameters are used in the errorest() in library ipred, as the following? errorest(Species ~ ., data=iris, model=randomForest, estimator = "cv", est.para=control.errorest(k=3), mtry=2)$err [1] 0.03333333 > errorest(Species ~ ., data=iris, model=randomForest, estimator = "cv",

Hello List, I`m trying to make prediction using a bagged tree with the package ipred. I tried to follow the manual but I`m getting an error message. Also browsing through the list-archive I didn`t find any hint. Maybe someone can help me? selbag <- bagging(SOIL_UNIT ~., data=traindat.bin, coob=TRUE) Error in dimnames(X) <- list(dn[[1L]], unlist(collabs, use.names = FALSE)) :

Hello everybody, i have already posted this message yesterday, but i didn't receive my posting. There i want to repeat it. >From time to time our nmbd daemon quits his job and the last time he did this he told us: [2006/01/25 15:56:02, 0] nmbd/nmbd.c:terminate(58) Got SIGTERM: going down... So my question is: What is the cause of this behaviour and in special what is happening when

Sorry for the tardy reply but I just found your posting incidentally today. To make long things short: You are right about the centering. We forgot to correct the intercept if center = TRUE. We lately found the problem ourself and fixed it in the current version (mboost 2.0-3). However the problem only occurred if you extracted the coefficients. As the intercept is rarely interpretable we

Dear all, can anybody help me with the program below? The function predict.lda seems to be defined but cannot be used by errortest. The R version is 1.7.1 Thanks in advance, Stefan ---------------- library("MASS"); library("ipred"); data(iris3); tr <- sample(1:50, 25); train <- rbind(iris3[tr,,1], iris3[tr,,2], iris3[tr,,3]); test <- rbind(iris3[-tr,,1],

Good morning, we recently observed a problem with importing S3 generics from a foreign package (without namespace), defining a S3 method in a package _with_ namespace and the `cleanEx()' function which is automatically generated and executed before examples are run by R CMD check. To be more precise. Package `strucchange' defines a S3 generic sctest <- function(x, ...)

When legend() is used with the angle argument as follows, not only the boxes beside the legend text, but also the whole legend box is filled with shading lines. I think this is not intended: plot(1:10) legend(8, 4, c("A", "B"), angle=c(10, 80), fill=NULL, density=20) I'd suggest as a fix (legend.R of R-1.5.0): 25c25 < rect2 <- function(left, top, dx, dy,

Problem: neither fg or bg nor color work properly in dotchart. version: R-1.7.1 for windows code which shows the errors: x <- matrix(rnorm(16),ncol=2,dimnames=list(paste("a",1:8,sep=""),c("before","afte r"))) dotchart(x,fg="blue",bg="lightgrey") dotchart(x,color=c("red","blue")) Dr Ian J Wilson Lecturer in

Full_Name: Mai Zhou Version: 1.9.1 OS: Win XP Professional Submission from: (NULL) (12.222.227.93) > power.t.test(n=25, delta=0.1, sig.level=1.1, strict=TRUE, type="one.sample") One-sample t test power calculation n = 25 delta = 0.1 sd = 1 sig.level = 1.1 power = 1.088311 alternative = two.sided ### power can never be