similar to: Weights in bagged regression trees

I am using bagging to perform Bagged Regression Trees on count data (bird abundance in Britain and Ireland, in relation to climate and land cover variables). Predictions from the final model are visually believable but I would really like a diagnostic equivalent to classification success that can be used to decide if a model is adequate. Whereas with classification data an error rate is returned,

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

Hi all I have produced a biplot for a PCA (see attached pdf) that I ran however the names of the variables which are placed at the end of the arrows overlap and are thus unreadable. Similarly some of the numbered points overlap. I was wondering if there was a way to edit the biplot to move the label names and if not what the best alternative is. Thanks Anna pca<-biodata[,3:10]

I have a set of data that is not normally distributed and for which I need to build a model. So, I tried the lrm function from the design-package. The first run went well, and I got the following results: Wald Statistics Response: RVCL2PROC.mott Factor Chi-Square d.f. P TTV.mott (Factor+Higher Order Factors) 69.01 4

Hi everyone! Could you please help me with the following assignment? My aim is to write a custom function that draws the plots of functions submitted by the user. The catch is, that we do not know the exact number of functions the user will select to draw. The program is relatively easy with one function, f.e sin: mf<- function(f,range,quality){ x<- seq(range[1],range[2],

Dear All Hopefully someone out there can point out what I am missing! I have a (large, several hundred) dataset of gardens in which over two years the presence/absence of a particular bird species is noted each week. I have good reason to believe there is a difference between the two years in the weekly proportion of gardens and would like to assess this, before going on to look in more detail at

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)) :

Good morning, I use SAS and R/S-Plus as my primary tools so I have a lot of experience with these programs. By far and away, SAS is superior for handling the "messy" datasets, but also the very large ones. I work at times with datasets in the hundreds of thousands (and on occasion, millions) of records. SAS, and especially PROC SQL, are invaluable for this. But once I get to

Hi, I would like estimate a model for function of production's Coob-Douglas using maximum likelihood. The model is log(Y)= beta[1]+beta[2]*log(L)+beta[3]*log(K). I tried estimate this model using the tools nlm ( ) and optim ( ) using the log-likelihood function below: > mloglik <- function (beta, Y, L, K) { + n <- length(Y) + sum ( (log(Y)-

I'm having the most weird problem with bagging function. For some unknown reason it does not improve the classification (compared to rpart), but instead gives much worse results ! Running rpart on my data gives error rate of about 0.3 and bagging, instead of improving this results, gives error rate of 0.9 !!! I'm running both rpart and bagging with exactly the same parameters, I even

Hello, can me please help anbody how it is possible unlist a "rpart.object.list" i.e. from bagging(ipred) to plot this "unique" several rpart.objects . ..i make attempts with unlist, get really atomic elements, but need only the different tree's ! Thanks for advance & regards,Christian -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

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,

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

Dear all, I have a problem with the function "bagged clustering" of package e1071. When I try to run the example of bagged clustering with the iris data : data(iris) bc1 <- bclust(iris[,1:4], 3, base.centers=5) I got the following message error : Loading required package: class Committee Member: 1(1) 2(1) 3(1) 4(1) 5(1) 6(1) 7(1) 8(1) 9(1) 10(1)Error in bclust(iris[, 1:4], 3,

Dear All: I'm a newbie to R and chemometrics. Now I'm trying apply bclust on fuzzy c-means like this: >bc1 <- bclust(iris[,1:4], 3, base.centers=20,iter.base=100, base.method="cmeans") Committee Member: 1(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)Erro r in bclust(iris[, 1:4], 3, base.centers = 20, iter.base = 100, base.method =

---------- Forwarded message ---------- Received: from brimstone.netspace.org (brimstone.netspace.org [128.148.157.143]) by blues.jpj.net (backatcha) with ESMTP id CAA13949; Fri, 14 Nov 1997 02:08:13 -0500 (EST) Received: from unknown@netspace.org (port 25452 [128.148.157.6]) by brimstone.netspace.org with ESMTP id <818-20257>; Fri, 14 Nov 1997 01:41:22 -0500 Received: from NETSPACE.ORG by

I was trying to produced bagged importance estimates of attributes in earth using the caret package with the following commands:   fit2 <- bagEarth(loyalty ~ ., data=model1, B = 10)   bagImpGCV <- varImp(fit2,value="gcv") My bootstrap estimates are produced however the second command "varImp" produces the following error:    Error in UseMethod("varImp") : no

R-users, Is there a function for ceiling to the nearest ten? a <- 1:10*4 a [1] 4 8 12 16 20 24 28 32 36 40 The resulting vector should look like this ("ceiling to the nearest ten") [1] 10 10 20 20 20 30 30 40 40 40 Thanks in advance Lauri

Hi there I have an interesting problem: My csv file is of array dimensions [12,50], but it was saved the wrong way: there should be only 11 colums. What happens now if I read it into R is that the whole data set is shifted ( in the first row, the last column contains already the first value of the supposed second row and so on...) how can I tell R to switch after 11 read values to the next row,