similar to: Multivariate Regression Trees: how to identify sample units?

Hi all, I am using the vegan package to run a prcincipal components analysis on forest structural variables (tree density, basal area, average height, regeneration density) in R. However, I could not find out how to extract factor loadings (correlations of each variable with each pca axis), as is straightforwar in princomp. Do anyone know how to do that? Moreover, do anyone knows

Dear Friends, Using package Vegan, I need to calculate Shannons Diversity index and Pielou's Evenness for a set of 20 study areas. Each area is represented by a matrix of 25 sample plots x tree species. The code is as following, where data stands for the data matrix of any of the 20 areas: S <- specnumber(data) H <- diversity(data) J <- H/log(S) I indexed the 20 areas by a

Hi, I am trying to learn time series, and I am attending a colleague's course on Econometrics. However, he uses e-views, and I use R. I am trying to reproduce his examples in R, but I am having problems specifying a AR(1) model. Would anyone help me with my code? Thanks in advance! Reproducible code follows: download.file("https://sites.google.com/a/proxima.adm.br/main/ex_32.csv

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

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 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

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,

Dear All, I would like to ask clarifications on the gower distnce matrix calculated by the function gdistin the library mvpart. Here is a dummy example: > library(mvpart) Loading required package: survival Loading required package: splines mvpart package loaded: extends rpart to include multivariate and distance-based partitioning > x=matrix(1:6, byrow=T, ncol=2) > x [,1]

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 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

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

R helpers, I am working with the R program performing multivariate regression trees (MRT). I have a matrix with species and environmental variables saved as a CSV file (sprot_matrix.csv), I have 42 species and 8 environmental variables (SECCHI+PH+TA+PTOT+NTOT+CHLA+AREA+ MEANDEP) for 104 samples Title SpA SpB SpC SpD Varible1 Variable2 Variable3 Sample1 Sample 2

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'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 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]]

I would like to know if is it possible implemet a partitioning tree using a function like rpart, or mvpart, and with formula a glm-object (as a logistic models) or a robust linear regression (as least sum of absolute errors). In this case, the appropriate "method" to use is "mrt"? Or another one? Thanks, Anna Maria Paganoni

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 --