similar to: binomial glm???

Dear All, 1. Does anyone have experience of running R on a server inside a Citrix shell - I'd like to get R onto the server and would be greatful for any tips or direction on the matter. 2. This may seem like a silly question so forgive my ignornace. Most of the data I currently work with is held on a number of Lotus Notes (LN) Databases (well it's called a DB here but it's really a

Dear all, The standard call to ARIMA in the base package such as arima(y,c(5,0,0),include.mean=FALSE) gives a full 5th order lag polynomial model with for example coeffs Coefficients: ar1 ar2 ar3 ar4 ar5 0.4715 0.067 -0.1772 0.0256 -0.2550 s.e. 0.1421 0.158 0.1569 0.1602 0.1469 Is it possible (I doubt it but am

Hi all, simple Q: how do I extract the upper and lower CI for predicted probabilities directly for a glm - I'm sure there's a one line to do it but I can't find it. the predicted values I get with the predict (.. "response") Thanks Gerard ********************************************************************************** The information transmitted is intended only for

Hi all, I have a multiple queing situation I'd like to simulate to get some idea of the distributions - waiting times and allocations etc. Does R has a package available for this - many years ago there used to be a language called "simscript" for discrete event simulation and I was wondering if R has an equivalent (or hopefully with graphics, something better!). Apologies if there

Dear all, sorry to bother you all with this but I've been trying to use the loglm in MASS package (v2.8.0) and cannot get any sensible output. I'm wondering am I doing something very foolish or missing something obvious. For example, I tried the documentation help(loglm) example - here's the code # Case 1: frequencies specified as an array. sapply(minn38,

Dear all, I've replicated the cheese tasting example on p175 of GLM's by McCullagh and Nelder. This is a 4 treatment (rows) by 9 ordinal response (cols) table. Here's my simple code: #### cheese library(MASS) options(contrasts = c("contr.treatment", "contr.poly")) y = c(0,0, 1, 7, 8,8,19, 8,1, 6,9,12,11, 7,6, 1, 0,0, 1,1, 6, 8,23,7,

Hi all, apologies if this is obvious - but I can't see it and would appreciate some quick help! the matrix mhouse is 26x3 and I'm computing odds ratios. The simple code below "should" compute the odds vector for every pair (325) i.e. 26C2 in cols 1 and 2. On the first i=1 outer loop the inner j loop runs from 2 to 26 ok and then I get the error (Error: subscript out of bounds)

I think SAS Macros has capability to call R, and execute it without it being in the picture anywhere. So you can use SAS Macros in a file called R.sas In this you can create a macro called %Describe that can call R , load Hmisc ,run the describe function Note you will need repeated use of %put in this %describe for the mapping to take place Use %INCLUDE to include that file in all SAS

Hello, firstly, I'm sorry for posting in the 3 lists ... I don't know if it is a bug or if some developer can help me. I comment my problem, I've used a game named FML (football manager live) with wine previously, it worked (months ago), I don't remember the version of FML client and wine version :-( I would want play to FML again, I've downloaded the new version of fml client

Hi, running the following code by itself runs as expected. ---------------------------------------------------------------------------- k <- 1 i <- 2 j <- 3 NumName <- varnames[num.cols[k]] FacNames <- varnames[fac.cols[c(i,j)]] tmp <- paste(FacNames[1],NumName,sep="~") fml <- formula(paste(tmp,FacNames[2],sep="|")) bwplot(fml, data

Hi, I have a problem in programming for bootstrapping. I don't know why it show the error message. Please see my code below: #'st' is my original dataset. #functions of 'fml.mlogl','pcopula.fam4','ltd','invltd' are already defined boot.OR<-function(data,i) { E=data[i,] ml1<-glm(c_VAsex90_bf ~ trt,family=binomial,data=E) ml2<-glm(c_VAsex90_bm ~

Hi ! First of all I have to advise you that I don't speak english as well as I whish. So, be lenient. I installed Ubuntu 9.04 on my laptop one month ago. I didn't make any changes, I used it with default settings. I managed to install Football Manager Live (FML) and it worked perfectly ! I installed wine (by apt-get - didn't make any changes either) and then ran the setup.exe from

Hello everybody, I'm reading the .td files defining the Cortex-A57 processor, which is a subtarget of AArch64 target, and there is something confusing me in the `AArch64SchedA57.td` file. In the top of `AArch64SchedA57.td`, various processor resource are defined, as follows ``` def A57UnitB : ProcResource<1>; // Type B micro-ops def A57UnitI : ProcResource<2>; // Type

Dear all, I was trying to use the R swig wrapper with R 2.7 and shogun ( http://www.shogun-toolbox.org ) but it fails completely, as in doesn't even compile and even after patching then though compiling - crashes... So I asked on swig-users/swig-devel CC'ing the potential R maintainer but I never received a reply. I now wonder if anyone here could help or would be willing to maintain

Hello R Users, How to make a variable equidistance with time i.e. how to interpolate a variable if it is not sampled at equal time interval. Many thanks, Regards, Yogesh [[alternative HTML version deleted]]

At a snail's pace I keep on translating an introduction to R into italian; I have reached the section describing the glm() function, in which some example code is presented. The very last line of code, before the beginning of the section on Poisson models is: ldp <- ld50(coef(fmp)); ldl <- ld50(coef(fmp)); c(ldp, ldl) which of course gives results 43.663 and 43.663; the correct code

At a snail's pace I keep on translating an introduction to R into italian; I have reached the section describing the glm() function, in which some example code is presented. The very last line of code, before the beginning of the section on Poisson models is: ldp <- ld50(coef(fmp)); ldl <- ld50(coef(fmp)); c(ldp, ldl) which of course gives results 43.663 and 43.663; the correct code

Hi, I am a biologist (relatively new to R) analyzing data which we predict to fit a power function. I was wondering if anyone knew a way to model piecewise functions in R, where across a range of values (0-x) the data is modeled as a power function, and across another range (x-inf) it is a linear function. This would be predicted by one of our hypotheses, and we would like to find the AICs

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Symptoms: curve with log x axis gets the wrong x limits (in 2.6.1, I believe introduced in this version). Credit goes to Mike McCoy for detecting the problem. Demonstration: x = 1:5 plot(x,5*exp(-x),xlim=c(0.1,1000),log="x") xvec = 10^seq(-1,3,length=100) lines(xvec,5*exp(-xvec)) curve(5*exp(-x),add=TRUE,col=2,lwd=3) I believe

Hi, I've got a matrix, Z, of values representing (as it happens) optical power at each pixel location. Since I know in advance I've got a single, convex peak, I would like to do a 2D parabolic fit of the form Z = poly((x+y),2) where x and y are the x,y coordinates of each pixel (or equivalently, the row, column numbers). Is there an R function that lets me easily implement that?