similar to: [OT] emacs / xemacs for unix without compile

Dear All, I finally have chance to have R install on our unix server. However, the system admin asked me if I prefer command-line or gui interface. I have experience with R on linux before but never use R on unix. Here are my questions that I need you guys help. 1) is there a good gui for R/unix like we do for windows and mac? 2) if the answer for 1) is yes, which one is better interms of

At the suggestion of many people, I have installed emacs on my linux (Fedora 8.0) computer with the intention of using emacs as window interface to R (2.6.0). I have gone though the emacs tutorial and don't see any information about how I should use emacs to run R. Can anyone suggest a document that I might read? In the past I have used R on a Windows XP system and used the built-in windowing

Dear Listers, My post might be somewhat OT. Currently, I am trying to use flexmix to build a finite mixture model. For instance, I am getting the prior probability and coefficients for each latent class from training data. Is there a way to get the posterior probablity and prediction of a new dataset? What I am thinking is to apply the prior prob and coefficient from training set to testing data

Hi, dear all, I just switch to vista (ultimate) and have heard there is some problem for the installation of xemacs on vista. Is there any insight or experience that you could share? I really appreciate any input. thank you so much!

Is there any implementation in R for finding the phase shift between two continuous signals. I would like to find the average phase shift for tow signals over two years. thanks Stephen -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted

Dear R users: I am wondering how to ask for *fixed* number of distributions under parameterized Gaussian mixture model. I know that em() and some related functions can predict the parameterized Gaussian mixture model. However, there seems no parameter to decide number of distributions to be mixed (if we known the value in advance). That is, assume I know the (mixed)data is from 3 different

I have a thirty thousand row data frame imported from excel and a 60,000 row data frame imported from excel. they share a common subset of the same data and I would like to combine the two into one data frame merged together on the data in common. I have looked at the help file for merge and intersect and cbind and rbind etc... And I can't figure it out. Thanks in advance Stephen --

This is the most basic question ever...I haven't used R in a couple years since college so I forget and haven't been able to find what I'm looking for in any of the manuals. I just need to figure out how to load a dataset into the program from excel! Thanks! CL [[alternative HTML version deleted]]

Hi everyone, please I'm having problem importing data from Stata and excel. Help me out. Thanks --------------------------------- [[elided Yahoo spam]] [[alternative HTML version deleted]]

Having just update to R 2.6.2 on my old Windows laptop I notice that the number of packages is growing exponentially and my usual approach of get-em-all may not be viable much longer. Has any thought been given to dividing "contributed" binaries into a recommended set, perhaps a couple of hundred, and the remained. That way one could install the recommended ones routinely and add in

Hi All, Sorry that I didn't provide enough information. I've been trying to import SAS xport files that contain multiple files using package foreign's read.xport. I first attempted this back in 2005 and had problems. Some of files that were present in the SAS xport file weren't being created in R. I submitted my problem to the community:

R 2.6.0 Windows XP A question about running a generalized linear model. I am running a glm with (1) a poisson distribution and a log link: family=poisson(link = "log") and an offset. I would like to know if I should express the offset as the log of the offset value, i.e. offset=log(NumUniqPt) or as: offset=NumUniqPt I suspect I need to use the log, bu t I can't find any

Here is my R Code x<-1:20000 y<-2:141 data.matrix<-data.matrix(data[,y])#create data.matrix variableprobe<-apply(data.matrix[x,],1,var) variableprobe #output variance across probesets hist(variableprobe) #displaying histogram of variableprobe write.table(cbind(data[1], Variance=apply(data[,y],1,var)),file='c://variance.csv') #export as a .csv file. Output in Excel all in 1

As a user of only R, I don't use much of the potential of ESS and Emacs. Without entering a religious feud, is there any reason I should use XEmacs rather than my current GNU Emacs? (I looked on the XEmacs site, but I didn't understand the programming issues they were talking about (over my head).) Martin Henry H. Stevens, Assistant Professor 338 Pearson Hall Botany Department Miami

I decided to try out Xemacs instead of Emacs in Linux (RH 7.2). After doing lots of configuration of Xemacs, I finally discovered a major problem. With Emacs, when I use R, I start Emacs twice (at least), in different viewports, once as emacs -f R and once as emacs myfile.R Then I try commands in the first one, and, when they work (which isn't very often), I cut the command with C-w,

Is there a package or function for multivariate garch model in R? I am having a hard time in locating one. Thanks for help in advance. -Young [[alternative HTML version deleted]]

Dear All, This is a question somewhat off-topic. Say, if I have known the number of components in the mixture, all the estimated parameters, prior probabilities, and so on for a finite mixture model, how might I compute the posterior probabilities of each case for a new dataset without observed response (Y)? I want to know the parametric form of such calculation such that I can calculate it

Dear R users, Simply my question is that how it is possible to generate some random numbers using rnorm( ) but in log transformed values. Thank you, Tobias --------------------------------- [[alternative HTML version deleted]]

Recently, I have been working with some data that look like two overlapping gaussian distributions. I would like to either 1) determine the mean and SD for each of the two distributions OR 2) get some (bayesian ?) statistic that estimates how likely an observation is to belong to the left-hand or right-hand distribution In case I'm using the wrong language, my data looks something like

Dear Lister, plot() is using the data range as the default limits of yaxis. Is there any way I can change the limits? I just look at the help of plot() and par() and couldn't find answers. Thanks. -- WenSui Liu (http://spaces.msn.com/statcompute/blog) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center