similar to: smv() in "e1071" and the BreastCancer data from "mlbench"

I am trying to use the survfit() function with the newdata argument to produce predicted survivor curves for a particular covariate profile. The main purpose of the plot will be to visualise the effect of snp1, coded 0 and 1. In my Cox model I have stratified by one variable, edu, and so I know I will automatically get a separate curve for each strata. My problem is how to deal with the

Dear R users, I am curious to know if someone has connected R with the Insight Segmentation and Registration Toolkit (www.itk.org). From the website... ITK is an open-source, cross-platform system that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and

dcemri 0.10 has been released on CRAN "dcemri" is (to the best of my knowledge) the first public-domain software package for the quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI or DWI). Data import and export is availble for ANALYZE or NIfTI data formats (sorry, no DICOM). Images are stored in neurological format regardless of the

dcemri 0.10 has been released on CRAN "dcemri" is (to the best of my knowledge) the first public-domain software package for the quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI or DWI). Data import and export is availble for ANALYZE or NIfTI data formats (sorry, no DICOM). Images are stored in neurological format regardless of the

Dear All, I'm getting a error while trying to apply the BreastCancer dataset (package=mlbench) to kknn (package=kknn) that I don't understand as I'm new to R. The codes are as follow: rm = (list = ls()) library(mlbench) data(BreastCancer) library(kknn) BCancer = na.omit(BreastCancer) d = dim(BCancer)[1] i1 = seq(1, d, 2) i2 = seq(2, d, 2) t1 = BCancer[i1, ] t2 =

TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PKPD modelling platform. This platform focuses on the transfer of knowledge from academia to the pharmaceutical industry and is a collaborative effort of four excellent academic institutes and six leading global pharmaceutical industries. Unique to this platform is the availability of shared databases on

After ctree builds a tree, how would I determine the direction missing values follow by examining the BinaryTree-class object? For instance in the example below Bare.nuclei has 16 missing values and is used for the first split, but the missing values are not listed in either set of factors. (I have the same question for missing values among numeric [non-factor] values, but I assume the answer

Hello everybody, this is my first request about R so I am sorry if I send it to a bad mail or if I am not very clear. So my problem is about the use of rfImpute from randomForest package. I am interested in imputations of missing values and I read that randomForest can make it. So i write the following code : set.seed(100); library(mlbench) library(randomForest) data(BreastCancer)

Last week Giovanni Parrinello posted a message asking why various packages were loaded when he loaded an .Rdata file. Brian Ripley replied saying he thought it was because the saved workspace contained a reference to the namespace of ipred. (Correspondence copied below). This begs the question: how did the reference to the namespace of ipred come to be in the .Rdata file? Brian did say it is

Last week Giovanni Parrinello posted a message asking why various packages were loaded when he loaded an .Rdata file. Brian Ripley replied saying he thought it was because the saved workspace contained a reference to the namespace of ipred. (Correspondence copied below). This begs the question: how did the reference to the namespace of ipred come to be in the .Rdata file? Brian did say it is

require(randomForest) rf.pred<-predict(fit, valid, type="prob") > rf.pred[1:20, ] 0 1 16 0.0000 1.0000 23 0.3158 0.6842 43 0.3030 0.6970 52 0.0886 0.9114 55 0.1216 0.8784 75 0.0920 0.9080 82 0.4332 0.5668 120 0.2302 0.7698 128 0.1336 0.8664 147 0.4272 0.5728 148 0.0490 0.9510 153 0.0556 0.9444 161 0.0760 0.9240 162 0.4564 0.5436 172 0.5148 0.4852 176 0.1730

Dear R-users, Recently, I am facing some problems when converting mlbench data into matrix format. library(mlbench) data(BostonHousing) X<- BostonHousing[,1:13] y<-BostonHousing[,14] I want to convert X and y into matrix form. I am getting these obvious errors... > t(X)%*%y Error in t(X) %*% y : requires numeric/complex matrix/vector arguments > t(as.matrix(X))%*%(as.matrix(y))

Hi. I'm trying to plot a pair of intertwined spirals and an svm that separates them. I'm having some trouble. Here's what I tried. > library(mlbench) > library(e1071) Loading required package: class > raw <- mlbench.spirals(200,2) > spiral <- data.frame(class=as.factor(raw$classes), x=raw$x[,1], y=raw$x[,2]) > m <- svm(class~., data=spiral) > plot(m,

I've made a package from some benchmark datasets for use with R and uploaded it to CRAN. Here's the Index entry: mlbench-0.1.tar.gz: A collection of artificial and real-world machine learning benchmark problems, including, e.g., the boston housing data from the UCI repository. Written/packaged by Fritz Leisch <Friedrich.Leisch at ci.tuwien.ac.at> Original data sets from

I've made a package from some benchmark datasets for use with R and uploaded it to CRAN. Here's the Index entry: mlbench-0.1.tar.gz: A collection of artificial and real-world machine learning benchmark problems, including, e.g., the boston housing data from the UCI repository. Written/packaged by Fritz Leisch <Friedrich.Leisch at ci.tuwien.ac.at> Original data sets from

I've made a package from some benchmark datasets for use with R and uploaded it to CRAN. Here's the Index entry: mlbench-0.1.tar.gz: A collection of artificial and real-world machine learning benchmark problems, including, e.g., the boston housing data from the UCI repository. Written/packaged by Fritz Leisch <Friedrich.Leisch at ci.tuwien.ac.at> Original data sets from

Hi, Evgenia and I have copied an updated version of the mlbench package to CRAN which contains several new data sets. We have also changed some of the variable names to avoid name conflicts. Best, -- ------------------------------------------------------------------- Friedrich Leisch Institut f?r Statistik Tel: (+43 1) 58801 10715 Technische

Hi, Evgenia and I have copied an updated version of the mlbench package to CRAN which contains several new data sets. We have also changed some of the variable names to avoid name conflicts. Best, -- ------------------------------------------------------------------- Friedrich Leisch Institut f?r Statistik Tel: (+43 1) 58801 10715 Technische

Hi all, I'm looking for an efficient solution (speed and memory) for the following problem: Given - a data.frame x containing numbers of type double with nrow(x)>ncol(x) and unique row lables and - a character vector y containing a sorted order labels Now, I'd like to sort the rows of the data.frame x w.r.t. the order of labels in y. example: x <- data.frame(c(1:4),c(5:8))

Apologies - I was not trying to correct you Brian, but to explore how the situation could arise. I'm sure you had a good idea why the namespace (or a reference to it) had been saved, but this was not clear to me and I thought, possibly not to others either. Thanks for putting me right over parent environments vs. enclosures - again I was not trying to correct you with the point I made there,