similar to: Random Forest - Strata

We are running kernel 2.6.18-164.6.1.el5 with exporting 3 aoe provided ext4 directories. For a couple of weeks we had a small number of users using the system with no issues, today we added 7 users and the system crashed and did not perform correctly since. Nov 23 10:20:03 sulphur rpc.idmapd[5199]: nfsdcb: id '-2' too big! Nov 23 10:42:25 sulphur nfsd[27306]: nfssvc: Setting version

Hi, I'm trying to make a partial plot with package randomForest in R. After I perform my random forest object I type partialPlot(data.rforest, pred.data=act2, x.var=centroid, "C") where data.rforest is my randomforest object, act2 is the original dataset, centroid is one of the predictor and C is one of the classes in my response variable. Whatever predictor or response class I

Hi, I am reading a large space-delimited text file into R (41 columns and many rows) and need to do run each row's values through another R object and then write to another text file. So, far using readLines and writeLines seems to be the best bet. I've gotten the data exchange working except each row is read in as one 'chunk', meaning the row has all values between two quotes

I've submitted a message twice this evening and it has not appeared. Are messages censored on this board? regards john --------------------------------------------------------- John A Coll, Director, Connection Software 391 City Road, LONDON, EC1V 1NE, UK Tel: 020 7713 8000 From outside UK Tel: +44 20 7713 8000 Fax: 020 7713 8001 Fax: +44 20 7713 8001 Email:

I have a loop that I iterate through in my view. <% coll.each do |itm| puts(itm.value) end %> How do I render the itm.value without using a <%= %> tag? Should puts not work? Joerg P.S. There is a good enough reason for me wanting to do this :-) -- Posted via http://www.ruby-forum.com/.

Hello All. I must be missing the really obvious here: mm <- function(d, i) median(d[i]) b1 <- boot(gravity$g, mm, R = 1000) b1 b2 <- boot(gravity$g, mm, R = 1000, strata = gravity$series) b2 Both b1 and b2 seem to have done (almost) the same thing, but it looks like the strata argument in b2 has been ignored. However, str(b1) vs str(b2) does show that the strata have been noted

Hello, I am running: R version 2.10.0 (2009-10-26) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 on a RedHat Linux box with 48Gb of memory. I am trying to create a model.matrix for a big model on a moderately large data set. It seems there is a size limitation to this model.matrix. > dim(coll.train) [1] 677236 128 > coll.1st.model.mat <-

I am attempting to emulate the VLOOKUP function from Excel in R. I want to compare one column (coll.minus.release) with another (release.days) to get the number of parasitoid released at that time (TotalParasitoids). for example: coll.minus.release release.days ParasitoidTotal -12 -266 1700 8 -259 1000 8

Just browsing the documentation, and searching the list came up short... I have some unbalance data and was wondering if, in a "0" v "1" classification forest, if these options might yield better predictions when the proportion of one class is low (less than 10% in a sample of 2,000 observations). Not sure how to specify these terms... from the docs, we have: classwt: Priors

Hello, I was hoping that someone could answer a few questions for me (the background is given below): 1) Can the coxph accept an interaction between a covariate and a frailty term 2) If so, is it possible to a) test the model in which the covariate and the frailty appear as main terms using the penalized likelihood (for gaussian/t frailties) b)augment model 1) by stratifying on the variable that

Hi all, I am aware that crr lacks the "friendly" command structure of functions such as cph. All is clear to me about including covariates until I want to include a stratification term in the competing risk framework (no nice strat command). I am still a bit of a novice in R - I am looking for an example to help me with this, but can't seem to find one. Any advice appreciated (no

[code]>require("survival") > coxph(Surv(futime,fustat)~age + strata(rx),ovarian) Call: coxph(formula = Surv(futime, fustat) ~ age + strata(rx), data = ovarian) coef exp(coef) se(coef) z p age 0.137 1.15 0.0474 2.9 0.0038 Likelihood ratio test=12.7 on 1 df, p=0.000368 n= 26, number of events= 12 > coxph(Surv(futime,fustat)~age, ovarian, subset=rx==1)

Dear All, I got a warning message "X matrix deemed to be singular" in Cox model with a time dependent coefficient. In my analysis, the variable "SEX" is a categorical variable which violate the PH assumption in Cox. I first used the survSplit() function to break the data set into different time intervals, and then fit the model. The procedures can be described as follows:

> -----Original Message----- > From: Brian Roy [mailto:mister.roy@gmail.com] > I do this with a Toshiba Strata DK280. The model before the CTX. You > shouldn't have any problem doing this with the CTX either. Assuming > you don't have SMDI integration with your voicemail (you didn't state > that you did), you just need the phones to send trailing digits, and > you

Hi everyone, Been reading up on Asterisk, and very interested in learning more. I've googled and read the archives and haven't found anything definitive on support for this phone system. We have a fairly large investment in the system itself and the phones, but would love to get away from the voicemail system it forces on us. Can anyone provide any feedback on using this system with

I've been using strata(sampling) and found that if the dataframe to be sampled ("data") consists of repeated measures that are not sorted in order the run will fail on a given stratum. Ordering the dataframe prior to using strata() eliminates this problem. Thanks, Eric -- Eric Vander Wal Ph.D. Candidate University of Saskatchewan, Department of Biology, 112 Science Place,

How can I get the log odds associated with the levels in strata() within a clogit() model? I'm running R-1.9.0 on a Linux platform. I am using clogit() to run a Rasch model in Item Response Theory in psychometrics. Symbolically, the model is: logit(p_{j,k}) = \log({\Pr(p_{j,k}) \over \Pr(1-p_{j,k})}) = \theta_j - \alpha_k, That is, the log odds of answering an test item correctly is

Hello, I am new to R, and am having trouble running a stratified bootstrap. My data set consists of 38 study sites in which I recorded the number of bird pairs. Each site has been classified as burned or mowed and for each of these two strata I would like to determine the precision of an overall density estimate. I can run an unstratified bootstrap without problem, but when I specify the strata I

Dear list members, I am working with a Cox ph model for the duration of unemployment. The event of interest in my analysis is getting employed. I have various background variables explaining this event: age, sex, education etc. I have multiple unemployment spells per person. I use a model with person-specific frailty terms in order to take into account the correlation of spells by the same

Sorry for the repost, but I've really been looking, and can't find any syntax direction on this issue... Just browsing the documentation, and searching the list came up short... I have some unbalanced data and was wondering if, in a "0" v "1" classification forest, some combo of these options might yield better predictions when the proportion of one class is low (less