similar to: Prediction accuracy from Bagging with continuous data

Has anyone any experience of applying observational weights in bagging? I am performing regression trees (continuous data on bird abundance) and need to account for sampling intensity. In a single tree, i.e. a call of rpart, I can specify weights either by having a separate vector called weights, or by a variable called weights in the dataframe under analysis. Both produce sensible (and identical)

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]

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

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

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,

Hi all, I've used R for basic programming and data management for a few years now. One of the things that I think could be improved is the data editor. Its a great feature and I use it alot by calling edit(data.frame); very useful to see if what you tried to do actually worked. However, one of the annoying things about it is that when you scroll down the window it doesnt show you all the

hi all, I often have a data frame like this example data.frame(sq=c(1,1,1,2,2,3,3,3,3),area=c(1,2,3,1,2,3,1,2,3),habitat=c("garden","garden","pond","field","garden","river","garden","field","field")) for each "sq" I have multiple "habitat"s each with an associated "area". I

Hi all, I have been trying to use zeroinfl() with the pscl package with R version 2.1.1. and with the newest versions of the contrib packages compatible with R 2.1.1. I have read the examples, the vignette and all the posts relating to zeroinfl() but I am still confused as to how to structure the model. Here is a small example; the error message is the same for big data sets

Hi all, I recently discovered how great win.metafile is for getting high resolution graphics into word. Having problems with specifying families though... #pdf works fine pdf("test.pdf",width=14,height=9) par(family="Helvetica") plot(1:10) text(4,4,"trial") dev.off() windows 2 #metafile doesnt like helvetica family

Hi all, This could be naivety/stupidity on my part rather than a problem with model output, but here goes.... I have fitted a fairly simple model m1<-glm(count~siteall+yrs+yrs:district,family=quasipoisson,weights=weight,data=m[x[[i]],]) I want to know if yrs (a continuous variable) has a significant unique effect in the model, so I fit a simplified model with the main effect ommitted...

Hi all, This is partly a statistical question as well as a question about R, but I am stumped! I have count data from various sites across years. (Not all of the sites in the study appear in all years). Each site has its own habitat score "habitat" that remains constant across all years. I want to know if counts declined faster on sites with high "habitat" scores. I can

Hi all, I would like to 1. Read in an arcmap image into R (I can export pretty much any type of image jpeg, bitmap etc from arcmap) 2. Use R to create a nice colour legend in the plot First of all, Is this possible? So far I'm stuck on point 1. I have tried read.pnm() from pixmap and read.jpeg() from rgl. the pnm example provided works fine x <-

Dear Sir, I am a R beginning user. I would like to apply the bagging algorithm to my data in order to classify a certain disease by Bagging Support Vector Machine Ensemble. My problem is that even if I am reading the book, looking at the examples in internet and available in R, learning a lot of theoretical things on about SVM esemble or Bagging method, I can't apply Bagged SVM esemble or

Does anybody know of a script of a simple method of converting mbox mail stores to maildirs? I'm moving from an old pop3 system to imap and after installing about half our office with mboxes have found that mbox does not support subfolders which some people like to use. Is there any simple way of converting? I can go to each individual account and "manually" convert swaping data

Hi, Is here anyone knows the difference between rapart and bagging when grow a CART tree? Thanks Qin

Hello! Does anyone know how to apply bagging for SVM? ( for example) I am using adabag package to execute bagging but this method, "bagging", works with classification trees. I would like to apply my bagging to other classifiers as SVM,RNA or KNN. Has anyone do it? Thanks!! [[alternative HTML version deleted]]

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

Hi, I'm analysing some anthropometric data on fifty odd skull bases. We know the gender of each skull, and we are trying to develop a predictor to identify the sex of unknown skulls. Rpart with cross-validation produces two models - one of which predicts gender for Males well, and Females poorly, and the other does the opposite (Females well, and Males poorly). In both cases the error

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