similar to: read.table - reading text variables as text

Hi I'm an R newbie. I can't seem to add new variables to data frames. Here are the stages (1) I import the data using read.csv. (2) I fix it using fix(data) (3) I create a new variable using spos<-tagPOS(stim,language="en",model=NULL,tagdict=NULL). (tagPOS is a function in the OpenNLP toolkit, which tags a string for part of speech. "stim" is a variable in the

Hi I used the package Natural Language Toolkit about a year ago to parse strings into parts of speech. However, I cannot find it on CRAN. Has it been withdrawn? Thanks Nick -- Lecturer in Speech and Language Pathology Room 1.9 King George VI Building Queen Victoria Road University of Newcastle-upon Tyne NE1 7RU 0191 222 8720 [[alternative HTML version deleted]]

Dear List Apologies for such a simple question: I have a vector of 738 elements, coded with values between 1 and 16 (but not containing 7, 10, 11 or 13) and wish to recode value 14 to 1, 4 to 2, 1 to 3, 2 to 4 and all other values to 5. I've been trying to use the replace function (in base) and %in%, but without success. Many thanks Roy

Hi, for example one could do it this way: v <- summary(fit)$coefficients[,4] the coefficient attribute is a matrix, and with the "4" you refere to the pvalue (at least in lm - don't know if summary(glm) produces sligthely different output). to skip the intercept (1st row): v <- summary(glmfit)$coefficients[-1,4] hope this helps, Arne -- Arne Muller, Ph.D.

Hello I'm very new to R (which is excellent), so apologies if this has already been raised. In the spdep package, I'm trying to undertake an autoregressive mixed model using the lagsarlm function. This is working fine, but there does not appear to be a method of including an explanatory variable without it automatically being included as a lagged term. I'm after something along the

Hello everyone, (This is my second question posted today on the R list). I am carrying out a competing risks analysis using the cuminc function...this takes the form: cuminc(ftime,fstatus,group) In my study, fstatus has 3 different causes of failure (1,2,3) there are also censored cases (0). "group" has two levels (0 and 1). I therefore have 6 different cumulative incidence curves:

Dear Rgurus, To my knowledge the best way to visualize the distribution of a discrete variable X is plot(table(X)) The problem which I have is the following. I have to discrete variables X and Y which distribution I would like to compare. To overlay the distribution of Y with lines(table(Y)) gives not satisfying results. This is the same in case of using density or histogram. Hence, I am

Dear R-help I have two separate experiments, one a repeated-measures design, the other a split-plot. In a standard ANOVA I have usually undertaken a multiple-comparison test on a significant factor with e.g TukeyHSD, but as I understand it such a test is inappropriate for repeated measures or split-plot designs. Is it therefore sensible to use Helmert contrasts for either of these designs?

Hi I have submitted a package (rioja) to CRAN. It checks OK for all R versions and OS's except r-release-macosx-ix86 where it fails when checking the examples. Specifically, it fails because R can't find the package vegan which is needed in a function. Here is the snippet from the check results: ### Begin snippet checking examples ... ERROR Running examples in 'rioja-Ex.R'

Hi Everybody, I am a newbie in R. I have a data in the form of a matrix which I want to make some 3D plots using R. There is some functions for instance hist() for 2D plots, but I cant find any function for 3D plots. Is there any function available in R for 3D plots? If so, is there any documention available on internet so that I can go through. With regards, Soumyadeep

Hello I'm very much a beginner on meta-analysis, so apologies if this is a trivial posting. I've been sent a set data from separate experimental studies, Treatment and Control, but no measure of the variance of effect sizes, numbers of replicates etc. Instead, for each study, all I have is the mean value for the treatment and control (but not the SD). As far as I can tell, this forces

I am trying to fit a nonlinear model using nlm(). My application of nlm() is a bit complicated. Here is the story behind the model being fit: The observer is trying to detect a signal corrupted by noise. On each trial, the observer gets stim=signal+rnorm(). In the simulation below I have 500 trials. Each row of stim is a new trial. On each trial, if the cross-correlation between the stim and the

Dear All, I am rather rusty with my R, but I recall being able to do something like plot(x1,...);plot(x2,add=TRUE,...) to plot two series on the same axes. Any suggestions how this may be done will be appreciated.

1)I am wandering how the following SQL statement can be written in R language w/o using sqldf: create table detail2 as select a.* from detail a, pdetail b where a.TDATE=b.TDATE and (a.STIM >= b.STIM and a.STIM <=b.MAXTIM) 2) when try if then in R it only applies to the 1st row & not to whole dataset like in SAS. How do you get round that? in SAS: data summary; set all1;

Using R (version 0.63.3) for MS windows, I try the following command > shell(paste("cd ",getenv("RHOME"),sep="")) which replies with an error message Too many parameters - FILES\RW0633 which appears to suggest that the space if the path name is causing difficulties to the cd command. getenv returns > getenv("RHOME") RHOME

Dear R-devlopers, I removed yesterday the R.2.1. installation from windows NT laptop and I am getting the following error when building a pacage with R.2.2 ---------- Making package msbase ------------ adding build stamp to DESCRIPTION making DLL ... make[3]: *** No rule to make target `d:/prog/r/rw2011/include/R.h', needed by `llogic.o'. Stop. .... I have no idea from where

Updating from centos 5.4 to 5.5 using an update rather than a rebuild, I get the following complaint from yum:- lvm2-2.02.56-8.el5_5.1.x86_64 from setup has depsolving problems --> Missing Dependency: device-mapper >= 1.02.39-1 is needed by package lvm2-2.02.56-8.el5_5.1.x86_64 (setup) This is from a local mirror, so checking the upstream feed in case the mirroring is incomplete I see

Greetings, I have recently come into some confusion over weather or not AIC results for comparing among models requires that they be nested. Reading Burnham & Anderson (2002) they are explicit that nested models are not required, but other respected statisticians have suggested that nesting is a pre-requisite for comparison. Could anyone who feels strongly regarding either position

Dear all, I am having quite a hard time in trying to figure out how to correctly spell out a model in R (a repeated-measures anova with a within-subject covariate, I guess). Even though I have read in the posting guide that statistical advice may or may not get an answer on this list, I decided to try it anyway, hoping not to incur in somebody's ire for misusing the tool. For the sake of

I'm trying to convert an S-Plus program to R.  Since I'm a SAS programmer I'm not facile is either S-Plus or R, so I need some help.  All I did was convert the underscores in S-Plus to the assignment operator <-.  Here are the first few lines of the S-Plus file:   sshc _ function(rc, nc, d, method, alpha=0.05, power=0.8,              tol=0.01, tol1=.0001, tol2=.005, cc=c(.1,2),