similar to: S4 methods bug in naming of slots (PR#3665)

Hi, I've got a problem building a contrast matrix for the Dunnet contrast in package multcopm. The following works fine: > summary(simtest(adiff ~ trial)) Simultaneous tests: Dunnett contrasts Data: adiff by trial Contrast matrix: trial1 trial2 trial3 trial4 trial5 trial2-trial1 -1 1 0 0 0 trial3-trial1 -1 0 1 0 0

Hi, i am using the n-way-call dialplan solution found on voip-info. i have added its entry in applicationmap of features.conf file. the problem is......its not working. to activate the n-way call i dial *0 but nothing happens. i have played around with dtmf and codec settings but no success. the extensions and sip configuration is below if you want to have a look. I dont have any clue why its not

Dear R-devel, I've written a numerical solver for SOCPs (second order cone programs) in R, and now I want to move most of the solver code into C for speed. I've written combined R/C packages before, but in this case I need to do matrix operations in my C code. As I have never done that before, I'm trying to write some simple examples to make sure I understand the basics. I am stuck

While installing my small package, I met a tricky problem. For clarity, let me explain it with the following simplified example. In ~/pkg/R/aclass.R, setClass("aclass", contains="bclass", representation(i="numeric")) In ~/pkg/R/bclass.R, setClass("bclass", representation(j="numeric")) After building a "pkg" package, the file

"C" appears to be an illegal name for a slot in an S4 class (example below). If this is a known limitation, and not a bug, it would be nice if it were caught by setClass. Paul Gilbert > setClass("testobj", representation ( C = "numeric")) [1] "testobj" > new("testobj", C= 2) Error in methodsPackageMetaName("C", name) :

Dear R-help list, I would like to perform multiple comparisons for lme. Can you report to me if my way to is correct or not? Please, note that I am not nor a statistician nor a mathematician, so, some understandings are sometimes quite hard for me. According to the previous helps on the topic in R-help list May 2003 (please, see Torsten Hothorn advices) and books such as Venables &

Dear r-helpers, I have a question about multiple testing. Here an example that puzzles me: All matrixes and contrast vectors are presented in treatment contrasts. 1. example: library(multcomp) n<-60; sigma<-20 # n = sample size per group # sigma standard deviation of the residuals cov1 <- matrix(c(3/4,-1/2,-1/2,-1/2,1,0,-1/2,0,1), nrow = 3, ncol=3, byrow=TRUE, dimnames =

I am using the latest version of R on a Windows machine and get the following error when I try to initialize a correlation structure with the function corAR1 in NLME. This example is taken from the book of Pinheiro and Bates, so it should work. What is going wrong? > library(nlme) > data(Orthodont) > cs1AR1 <- corAR1(0.8, form= ~1 | Subject) > cs1AR1 <- initialize(cs1AR1, data =

Dear list, As a reply to my recent mail: > simint and TukeyHSD work for aov objects. > Can someone point me to similar functions for lme objects? Douglas Bates wrote There aren't multiple comparison methods for lme objects because it is not clear how to do multiple comparisons for these. I don't think the theory of multiple comparisons extends easily to lme models. One could

I have run the following logistic regression model: options(contrasts=c("contr.treatment", "contr.poly")) m <- glm(wolf.cross ~ null.cross + feature, family = "binomial") where: wolf.cross = likelihood of wolves crossing a linear feature null.cross = proportion of random paths that crossed a linear feature feature = CATEGORY of linear feature with 5 levels:

I'm in the very initial stage of expanding the formula processing in my quantile regression function rq() to handle additive nonparametric components, say qss(x), or qss(x,z). I need some advice about strategy for formula processing. My initial foray was to use: terms(formula,specials="qss") and then modify the components of the resulting terms.object. But in changing formula

Hi! I use simtest fonction of multcomp package to compile a Dunnett's test. I have 10 treatments and one control group, so i create a matrix with: m<-matrix(0,10,11) m[1,1]<--1 m[1,2]<-1 m[2,1]<--1 m[2,3]<-1 m[3,1]<--1 m[3,4]<-1 m[4,1]<--1 m[4,5]<-1 m[5,1]<--1 m[5,6]<-1 m[6,1]<--1 m[6,7]<-1 m[7,1]<--1 m[7,8]<-1 m[8,1]<--1 m[8,9]<-1

Dear R-helpers: My question is how do I efficient and valid correct for multiple tests in a repeated measurement design: Suppose we measure at two distinct visits with repeated subjects a treatment difference on the same variable. The treatment differences are assessed with a mixed model and adjusted by two methods for multiple tests: # 1. Method: Adjustment with library(multcomp)

I think the code is part of the RTAQ package but is not included in it, as I obtained it from https://r-forge.r-project.org/scm/viewvc.php/pkg/RTAQ/R/HAR_model.R?view=markup&root=blotter&sortby=author&pathrev=1028. It is not my code and I make no claim to other's good work, and apologize if I should even be posting it I am not sure, but in the transform function it allows to

Hi R, Please solve my problem........... I am extracting Bloomberg data from R, in a loop. R is getting fatigued by doing this process and gives some errors. I introduced sleep function. Doing this sometimes I get the results and sometimes not. I even noticed that if I give complete rest for R (don't open R window) for 1 day and then run my code with the sleep function, then the

Hi, I am trying to achieve 3-way conferencing taking hint from wiki link http://www.voip-info.org/wiki/view/Asterisk+n-way+call+HOWTO Here is the scenario: 1. user "user1" calls user "user2" 2. "user1" then presses the feature code "*0" to redirect "user2" to conference room 300 3. "user1" then dials the user "user3" 4.

Under R2.10.0 beta (2009-10-14 r50082) my .First does not run reliably. I reported this last week, but not reproducibly, and it seemed to go away, so I thought it might be installation-related. But it has now recurred reproducibly, at least on my machine. The website ftp://ftp.csiro.au/MarkBravington contains two .RData files each containing (only) a .First. One of them does what it should, and

I am working with xts dependent data, and my code is as follows (the problem is explained throughout): dat <- getdat("prices") dat <- read.zoo(dat, sep = "",format="%d/%m/%Y %H:%M", tz="", FUN=NULL, regular=TRUE, header=TRUE, index.column=1, colClasses=c("character", "numeric")) dat <- as.xts(dat)

Dear list, I have been studying R and I would like the aid of more experienced to solve the problems of the analysis below: r = gl(3, 8, label = c('r1', 'r2', 'r3')) e = rep(gl(2, 4, label = c('e1', 'e2')), 3) y = c(26.2, 26.0, 25.0, 25.4, 24.8, 24.6, 26.7, 25.2, 25.7, 26.3, 25.1, 26.4, 19.6, 21.1, 19.0, 18.6, 22.8, 19.4, 18.8, 19.2, 19.8, 21.4,

Dear R community, I performed a generalized linear mixed model using glmmPQL (MASS library) to analyse my data i.e : y is the response with a poisson distribution, t and Trait are the independent variables which are continuous and categorical (3 categories C, M and F) respectively, ind is the random variable. mydata<-glmmPQL(y~t+Trait,random=~1|ind,family=poisson,data=tab) Do you think it