similar to: regression in R

Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working

Dear R community I have tried to run the diagnostics on my lm object with the gvlma package but it gave me an error with the following message: Non compatible arguments I post here my syntax and session info: RegreC3<-lm(Classification_Score~C3L+Age_+Dx,data=DB1)summary(RegreC3) library(gvlma)gvmodel <- gvlma(RegreC3) R version 2.13.1 (2011-07-08)Platform: i386-pc-mingw32/i386 (32-bit)

Hi, Using the example data from library(gvlma) library(gvlma) data(CarMileageData) CarMileageNew <- CarMileageData[,c(5,6,3)] ?lst1 <- list() ?y <- c("NumGallons", "NumDaysBetw") ?for(i in seq_along(y)){ ?lst1[[i]] <- gvlma(lm(get(y[i])~MilesLastFill,data=CarMileageNew)) ?lst1} pdf("gvlmaplot.pdf") ?lapply(lst1,plot) dev.off() You could also use

Dear List I just downloaded and installed R 2.12.0 and then installed R Commander . First it got RCmdr and Car, and then suggested for other packages for utilizing the full functionality- I clicked yes! I got 140 packages installed!!! Cran Mirror was UCLA... Here is the list. Is this intentional- I can see some packages like snow and multicore which are desirable but quite optional.(see list

Dear all, I am stuck with tracking down an error I get from R CMD check (Windows, R 2.4.0, same error for R 2.2.1): when running R CMD check over a modified version of package relaimpo, I get the following output in install.out: preparing package relaimpo for lazy loading Loading required package: MASS Loading required package: boot Error in parse(file, n, text, prompt) : syntax error at 2193:

I am currently using the relaimpo package to estimate the relative importance of regressors (N= 4000): > m1 <- lm(y ~ x1+x2+x3+x4+x5+, data=data) > calc.relimp(m1, rela=TRUE) > m2=boot.relimp(m1, boot = 500, rela=TRUE, type="lmg") > booteval.relimp(m2) > plot(booteval.relimp(m2)) In a new dataset with 3 measurement points (0,6,12 weeks), I want to perform a similar

Dear R-developers, I'm experiencing a problem with having an example run under R 2.6.1 RC (downloaded and installed today, r43513), which does not occur on R 2.6.0: The new version of package relaimpo does list package survey under "Depends", and an example directly (i.e. not only from within a function of relaimpo) uses function svydesign from package survey. Package survey is

I'm having trouble getting the relaimpo package to use a covariance matrix as input. I'm getting an error message that reads as follows: Error in eval(m$weights, data, parent.frame()) : numeric 'envir' arg not of length one I'm guessing there is something wrong with the structure of my covariance matrix, but it looks fine to me. Pardon my R ignorance if this is an easy

Hello! I am trying test my observed data against the null-hypothesis that different items from a psychological questionnaire contribute equally to the metric dependent variable that measures problems (sum score of a questionnaire). That is, I am interested in relative strength of the predictors. Predictor items of the questionnaire are on a scale from 0-3, and technically ordinal, although most

Hi, I'm trying to compile the package biglm, but when I build it with R CMD build biglm, it failed : C:\LOCAL\c-dutang\code\R\biglm2>R CMD build biglm * checking for file 'biglm/DESCRIPTION' ... OK * preparing 'biglm': * checking DESCRIPTION meta-information ...C:/DOCUME~1/c-dutang/Local: Can't op n C:/DOCUME~1/c-dutang/Local: No such file or directory

Dear R-help and ROCR developers (Tobias Sing and Oliver Sander) - I think my first question is generic and could apply to many methods, which is why I'm directing this initially to R-help as well as Tobias and Oliver. Question 1. The plot function in ROCR will average your cross validation data if asked. I'd like to use that averaged data to find a "best" cutoff but I

I'm trying to use ROCR to create a simple cutoff vs recall plot (recall at p) on the example ROCR.simple dataset: library(ROCR) data(ROCR.simple) pred <- prediction(ROCR.simple$predictions, ROCR.simple$labels) perf <- performance(pred, "rec") plot(perf) But R crashes on me on the last line. I'm using R 2.14.1, ROCR 1.0-4. ?Any ideas? Thanks in advance. -- Yang Zhang

All, I'm trying again with a slightly more generic version of my first question. I can extract the plotted values from hist(), boxplot(), and even plot.randomForest(). Observe: # get some data dat <- rnorm(100) # grab histogram data hdat <- hist(dat) hdat #provides details of the hist output #grab boxplot data bdat <- boxplot(dat) bdat #provides details of the boxplot

I am trying to use package ROCR to analyze classification accuracy, unfortunately there are some problems right at the beginning. Question 1) When I try to run demo I am getting the following error message > library(ROCR) > demo(ROCR) > if(dev.cur() <= 1) .... [TRUNCATED] Error in get(getOption("device")) : wrong first argument When I issue the command > dev.cur() it

I am trying to figure out why 'biglm' can handle large data set... According to the R document - "biglm creates a linear model object that uses only p^2 memory for p variables. It can be updated with more data using update. This allows linear regression on data sets larger than memory." After reading the source code below? I still could not figure out how 'update'

Dear all, I am working on a large dataset and need to use biglm() to perform OLS regressions. I have detected significant ARCH effects which I try to account for using the Newey-West correction. So far, I have worked with NeweyWest() in the sandwich package. NeweyWest() however seems to be unable to handle an object of class "biglm". Looking into the code, I figured out that

Hello folks, I am very excited to have discovered R and have been exploring its capabilities. R's regression models are of great interest to me as my company is in the business of running thousands of linear regressions on large datasets. I am using biglm to run linear regressions on datasets that are as large as several GB's. I have been pleasantly surprised that biglm runs the

Dear R-help This is a follow-up to my previous post here: http://groups.google.com/group/r-help-archive/browse_thread/thread/d9b6f87ce06a9fb7/e9be30a4688f239c?lnk=gst&q=dobomode#e9be30a4688f239c I am working on developing an open-source automated system for running batch-regressions on very large datasets. In my previous post, I posed the question of obtaining VIF's from the output of

Hello colleagues, I have tried to use the package biglm. I want to specify a multivariate regression with a weight. I have imported a large dataset with the library(bigmemory). I load the library (biglm) and specified a regression with a weight. But I get everytime a error message like ?object not found? or ?`weights' must be a formula? or "error in eval(expr, envir, enclos)". I

Hello all, I have two problems with the ROCR package. First Problem: the add=TRUE option does not work for plotting performance objects The following code is taken from the reference manual (example for ROCR.hiv, page2) data(ROCR.hiv) attach(ROCR.hiv) pred.svm <- prediction(hiv.svm$predictions, hiv.svm$labels) perf.svm <- performance(pred.svm, 'tpr', 'fpr') pred.nn <-