similar to: mvpart versus SPSS

The package mvpart is now available. mvpart includes partitioning based on (1) multivariate numeric responses and (2) dissimilarity matrices. The package mvpart is a modification of rpart -- -- authors of original: Terry M Therneau and Beth Atkinson <atkinson at mayo.edu>, and R port of rpart Brian Ripley <ripley at stats.ox.ac.uk>. Includes some modified routines from vegan --

The package mvpart is now available. mvpart includes partitioning based on (1) multivariate numeric responses and (2) dissimilarity matrices. The package mvpart is a modification of rpart -- -- authors of original: Terry M Therneau and Beth Atkinson <atkinson at mayo.edu>, and R port of rpart Brian Ripley <ripley at stats.ox.ac.uk>. Includes some modified routines from vegan --

Dear R friends- I'm attempting to generate a regression tree with one gradient predictor and multiple responses, trying to test if change in size (turtle.data$Clength) acts as a single predictor of ten multiple diet taxa abundances (prey.data) Neither rpart or mvpart seem to allow me to do multiple responses. (Or if they can, I'm not using the functions properly.) > library(rpart)

Dear R community, I am analyzing plant communities with the function mvpart, using a dissimilarit matrix as input. The matrix is calculated with the funtion gdist. fit <- mvpart(gdist (ba12[,18:29], meth="maximum", full=TRUE, sq=F) ~ beers + slope_dem + elev_dem+ plc_dem + pr_curv+ +curv+max_depth+doc_rocks+ abandon+land_use+ca_old, data=ba12, xv="p") This

Dear r-list: I am using rpart to build a tree on a dataset. First I obtain a perhaps too large tree: > arbol.bsvg.02 <- rpart(formula, data = bsvg, subset=grp.entr, control=rpart.control(cp=0.001)) > arbol.bsvg.02 n= 100000 node), split, n, loss, yval, (yprob) * denotes terminal node 1) root 100000 6657 0 (0.93343000 0.06657000) 2) meses_antiguedad_svg>=10.5 73899 3658

Hi all, I am fairly new to R and I am trying to run mvpart and create a MRT using explanatory variables and covariables. I've been following the procedures in Numerical Ecoogy with R. The command (no covariables) which works fine - ABUNDTMRT <- mvpart(abundance ~ .,factors,margin=0.08,cp=0,xv="1se",xval=nrow(abundance),xvmult=100,which=4) where abundance is 4th root

Still about the mvpart. Is there any way I can control for the number of elements in each node in the function mvpart? Specifically, how can I ask partition to ignore node with elements less than 10? Thanks! -Shu

Hello, I'm using mvpart option xv="1se" to compute a regression tree of good size with the 1-SE rule. To better understand 1-SE rule, I took a look on its coding in mvpart, which is : Let z be a rpart object , xerror <- z$cptable[, 4] xstd <- z$cptable[, 5] splt <- min(seq(along = xerror)[xerror <= min(xerror) + xvse * xstd]) I interprete this as following: the

HI, Dear R community, I am writing the following function to create one data set(*tree.pred*) and one vector(*valid.out*) from loops. Later, I want to use the data set from this loop to plot curves. I have tried return, list, but I can not use the *tree.pred* data and *valid.out* vector. auc.tree<- function(msplit,mbucket) { * tree.pred<-data.frame()

Dear all, I was wondering if there is a simple way to avoid printing the multiple cross-validation automatic output to the console of recursive partitionning functions like rpart or mvpart. For example... > data(spider) > mvpart(data.matrix(spider[,1:12])~herbs+reft+moss+sand+twigs+water,spider,xv="1se",xvmult=100) *X-Val rep : 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

-----Original Message----- From: Vayssi?res, Marc Sent: Tuesday, June 20, 2006 9:35 AM To: 'r-help-bounces at stat.math.ethz.ch' Subject: RE: [R] multivariate splits Glen De'ath's package for R is on cran! It is called mvpart, see: http://cran.cnr.berkeley.edu/doc/packages/mvpart.pdf Cheers, Marc Vayssi?res -----Original Message----- From: r-help-bounces at stat.math.ethz.ch

Hello everyone, I am currently using the mvpart package and would like to change the color scheme it uses, and was hoping someone could help me out. All of the papers I have found have used a grayscale but I can't seem to figure out how they did that! Currently, mvpart plots barplots in a repeating sequence of 3 shades of blue. So if you have 6 response variables the same shade of blue is used

Dear All, I have a question regarding predict.rpart. I use rpart to build classification and regression trees and I deal with data with relatively large number of input variables (predictors). For example, I build an rpart model like this rpartModel <- rpart(Y ~ X, method="class", minsplit =1, minbucket=nMinBucket,cp=nCp); and get predictors used in building the model like

Hi. I uses rpart to build a regression tree. Y is continuous. Now, I try to predict on a new set of data. In the new set of data, one of my x (call Incoterm, a factor) has a new level. I wonder why the error below appears as the guide says "For factor predictors, if an observation contains a level not used to grow the tree, it is left at the deepest possible node and

Hello, When trying to run mvpart either specifying my own parameters or using the defaults, I get the following error: Error in all(is.leaf) : unused argument(s) (c(FALSE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE)) As far as I can tell, is.leaf is part of the dendrogam package, so I'm assuming there's some problem with the graphical parameters. However running same formula and data

Dear R's I'm trying to use specific rather than random cross-validation groups in mvpart. The man page says: xval Number of cross-validations or vector defining cross-validation groups. And I found this reply to the list by Terry Therneau from 2006 The rpart function allows one to give the cross-validation groups explicitly. So if the number of observations was 10, you could use

Dear all, I'm getting an error in one of the stock examples in the 'mvpart' package. I tried: require(mvpart) data(spider) fit3 <- rpart(gdist(spider[,1:12],meth="bray",full=TRUE,sq=TRUE)~water+twigs+reft+herbs+moss+sand,spider,method="dist") #directly from ?rpart summary(fit3) ...which returned the following: Error in apply(formatg(yval, digits - 3), 1,

Brian The following (which is new to rw1030) occurs with both Windows 98 & Windows ME. I have not tested behaviour under Unix or Linux, but I expect it is no different. text.rpart() prints unwanted NAs (presumably in the splitting criterion position) on terminal nodes. Criterion <- factor(paste("Leaf", 1:5)) Node <- factor(1:5)

R-users E-mail: r-help@r-project.org Hi! R-users. http://finzi.psych.upenn.edu/R/library/mvpart/html/xpred.rpart.html says: data(car.test.frame) fit <- rpart(Mileage ~ Weight, car.test.frame) xmat <- xpred.rpart(fit) xerr <- (xmat - car.test.frame$Mileage)^2 apply(xerr, 2, sum) # cross-validated error estimate # approx same result as rel. error from printcp(fit) apply(xerr, 2,

Hello, I'm using the R package called mvpart, which is about the multivariate regression trees. The function I wrote is: mrt1<- mvpart(coefmat~sChip+sScreen+sMem,data=mixdata, xv="pick", plot.add=TRUE,uniform=TRUE,which=4,all=TRUE,xadj=2,yadj=2,rsq=TRUE,big.pts=TRUE,wgt.ave.pca=TRUE,legend=TRUE,bars=F, pca=TRUE) where "coefmat" is a matrix(of dimension N*K) to store