similar to: if function and apply

Simple problem but I don't see the answer. I'm trying to clean up some data I have 120 columns in a data.frame. I have one value in a column named "blaw" that I want to change. How do I find the coordinates. I can find the row by doing a subset on the data.frame but how do I find out here "blaw " is in columns without manually counting them or converting names(Df) to a

Hello All, I have a doubt regarding the fault tolerance of the rsync tool. What happens if the network goes down for some time and comes back after few seconds? Will rsync retry ? If yes, how many times/ how much time it will keep retrying ? How to ensure the completion of the rsync operation when there are network break ups? thanks for any help. -- Regards, Ravi.Thati -------------- next

Dear list, I have updated to version R-2.10.0. When I try to load the RSPerl library I get the following error: > library(RSPerl) Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared library '/usr/local/lib/R/library/RSPerl/libs/RSPerl.so': /usr/local/lib/R/library/RSPerl/libs/RSPerl.so: undefined symbol: boot_DB_File__Glob Error: package/namespace load failed

Dear R Users, Am using lm() with contrasts as below. If I skip the contrasts() statement, I get the coefficient names to be > names(results$coef) [1] "(Intercept)" "VarAcat" "VarArat" "VarB" which are much more meaningful than ones based on integers. Can anyone tell me how to get R to keep the coefficient names based on the factor levels

I am having a problem with Samba 3.0.20b runninn on Fedora core 4, with a 2.6.11-1.1369_FC4smp kernel. Each time I open a connection a new smbd process is forked. That is fine, but then that process never goes away, even after the client has disconnected. Even though there are only a few clients who make an smb connection to the server in question, dozens and dozens of smbd processes are

For example, c("dog.is.an.animal", "cat.is.an.animal", "rat.is.an.animal"). How can I identify the common prefix is ".is.an.animal" and delete it to give c("dog", "cat", "rat") ? Thanks _________________________________________________________________ [[alternative HTML version deleted]]

Ronaldo, Further to my previous posting on your Glycogen nested aov model. Having read Douglas Bates' response and Reflected on his lmer analysis output of your aov nested model example as given.The Glycogen treatment has to be a Fixed Effect.If a 'treatment' isn't a Fixed Effect what is ? If Douglas Bates' lmer model is modified to treat Glycogen Treatment as a purely

Hi, I''m trying to understand the lme output and procedure. I''m using the Crawley''s book. I''m try to analyse the rats example take from Sokal and Rohlf (1995). I make a nested analysis using aov following the book. > summary(rats) Glycogen Treatment Rat Liver Min. :125.0 Min. :1 Min. :1.0 Min. :1 1st Qu.:135.8

Dear all, During my pre-R era I tried (yes, tried) to understand mixed models by working through the 'rat example' in Sokal and Rohlfs Biometry (2000) 3ed p 288-292. The same example was later used by Crawley (2002) in his Statistical Computing p 363-373 and I have seen the same data being used elsewhere in the litterature. Because this example is so thoroughly described, I thought

Your response nicely clarifies a question that I've had for a long time, but which I've dealt with by giving each subject a unique label. Unless I'm missing something, both techniques should work as the toy example below gives exactly the same output in all 3 cases below (forgetting about the convergence problem). Would there be a reason to prefer labeling the levels one way or

Hi All, I would like to ask a question on fixed and random effecti in lme. I am fiddlying around Mick Crawley dataset "rats" : http://www.bio.ic.ac.uk/research/mjcraw/statcomp/data/ The advantage is that most work is already done in Crawley's book (page 361 onwards) so I can check what I am doing. I am tryg to reproduce the nested analysis on page 368:

Dear list,I have read really a lot the past few days, but I haven't found a matching solution for my problem.I have R 2.9.2 on Windows XP and MikTex 2.8 installed.What I want to do is to automate the sweave file generation.I thought I could use the R2Sweave, RweaveLatex, and Sweave in a combination so thatI won't need to do anything.Perhaps some minor modifications at the last step.My

Hi! All, I am working on a dataset 'rat' with dimension 20500x363. I have calculated pca of samples (columns). Now I am trying to plot first two principle components with specified columns in different color. I have done following so far: > dim(rat) [1] 20500 363 >#specifying columns to be colored in red >

As the freeze for Debian sarge slowly approaches I want to make sure the Dovecot packages are in as good condition as possible. I see there have been a number of patches since 0.99.10. I have added the following patches: * segfault when user home directory is empty * Proper PAM service name * Make suid work on 2.6 kernels Any other patches thatI ought to add. Or better yet, will there be a

Hi i would like to use some graphs or tables to explore the data and make some sensible guesses of what to expect to see in a glm model to assess if toxin concentration and sex have a relationship with the kill rate of rats. But i cant seem to work it out as i have two predictor variables~help?Thanks.:) Here's my data. >

Hi All, I have written script to download a directory from remote machine which contains the always the updated data. I want to download that directory onto my local machine periodically with --link-dest option to my old download directory. I have automated the script using " expect scripting" Following script I have written: $> cat ravi.ex #!/usr/bin/expect -- set LDEST

Dear R-listers, Does anybody know what is the correct source of "rats" dataset in survival package? The help gives the following information: Rat data from survival5 Description: 48 rats were injected with a carcinogen, and then randomized to either drug or placebo. The number of tumors ranges from 0 to 13; all rats were censored at 6 months after randomization.

When I try to run the example from Variogram with an lme object, I get an error (although summary works): R : Copyright 2005, The R Foundation for Statistical Computing Version 2.2.1 (2005-12-20 r36812) ISBN 3-900051-07-0 ... > fm1 <- lme(weight ~ Time * Diet, BodyWeight, ~ Time | Rat) Error: couldn't find function "lme" > Variogram(fm1, form = ~ Time | Rat, nint =

Hi, When I call the *switch* function first time, it works. but when I call it at the second time, it does nothing. The version I use is R version 2.9.0 Under development (unstable) (2009-02-21 r47969) here is the output: > organism="human" > species <- switch(organism, human <- "Hs", fly <- "Dm", mouse <-

Dear friends - I'm having troubles with nlme fitting a simplified model as shown below eliciting the error Error in chol.default((value + t(value))/2) : ? the leading minor of order 1 is not positive definite - I have seen the threads on this error but it didn't help me solve the problem. The model runs well in brms and identifies the used parameters even with fixed effects for TRT?