similar to: barplot and pca plot in mvpart/rpart

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

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

>>>>> Shu Fai Cheung >>>>> on Thu, 6 Jul 2023 17:14:27 +0800 writes: > Hi All, > I would like to ask two questions about printCoefmat(). Good... this function, originally named print.coefmat(), is 25 years old (in R) now: -------------------------------------------------------------------- r1902 | maechler | 1998-08-14 19:19:05 +0200 (Fri,

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 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

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,

Hello all, When attempting a classification tree using mvpart, I get the following error: > thesis2.mvp=mvpart(bat_sp~., data=alltrees.df) Error in all(keep) : unused argument(s) (c(TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,

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

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

Hi, I'd like to perform Dufrene-Legendre Indicator Species Analysis for a multivariate regression tree. However I have problems with arguments of duleg(veg,class,numitr=1000)function. How to obtain a vector of numeric class memberships for samples, or a classification object returned from mvpart? thanks in advance -- Best regards, Agnieszka Strzelczak

Dear R-list, I am using the rpart/mvpart-package for selecting a right-sized regression tree by 10-fold cross-validation. My question: Is there a possibility to find out for every observation in which of the ten folds it is lying? I want to use the same folds for validating another regression method (moving averages) in order to choose the better one. Thanks a lot, Pedro

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

I am working with some survival data with missing values. I am using the mice package to do multiple imputation. I have found code in this thread which handles pooling of the MI results: https://stat.ethz.ch/pipermail/r-help/2007-May/132180.html Now I would like to plot a survival curve using the pooled results. Here is a reproducible example: require(survival) require(mice) set.seed(2) dt

I have created a multivariate regression tree using mvpart, with 3-4 responses. Though the plot shows bargraphs for each response, I would like to have the VALUES of the responses printed or indicated (via a scale or something) alongside the bargraph. Is this possible ?? Thanks, Manjunath [[alternative HTML version deleted]]

Hello: I am using rpart and would like more background on how the splits are made and how to interpret results - also how to properly use text(.rpart). I have looked through Venables and Ripley and through the rpart help and still have some questions. If there is a source (say, Breiman et al) on decision trees that would clear this all up, please let me know. The questions below pertain to a

Hi All, I would like to ask two questions about printCoefmat(). First, I found a behavior of printCoefmat() that looks strange to me, but I am not sure whether this is an intended behavior: ``` r set.seed(5689417) n <- 10000 x1 <- rnorm(n) x2 <- rnorm(n) y <- .5 * x1 + .6 * x2 + rnorm(n, -0.0002366, .2) dat <- data.frame(x1, x2, y) out <- lm(y ~ x1 + x2, dat) out_summary <-

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@biostat.ku.dk # ###################################################### Under R version 0.6.51 the following A_c(13,9,15,5,25,15,3,9,6,12) B_c(42,24,41,19,27)

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 --

I have a question relating to mvpart, which I hope you can answer. We recently conducted a study using TBR. In our first study, we used "regular" TBR in SPSS to model 1 dependent variable. Note we have a relatively small data-set of 100 cases. In SPSS, we used a minimum change of improvement smaller than 0.000001 as a stopping rule. Also, we chose the 1SE "rule", set the