similar to: Exact Confidence Intervals for the Ration of Two Binomial

Hello everyone, I wanted to ask what will be a good editor to write R scripts in Fedora 7. Tony [[alternative HTML version deleted]]

I recently came across a flyer from REvolution Computing, and I wanted to ask if this is R going private? Tony. [[alternative HTML version deleted]]

Hello everyone, I'll to request some input on what is available for use as an R/Excel interface; any help will be appreciated. Tony. [[alternative HTML version deleted]]

Hello. We are trying to install R on our network, and I wanted to ask if there is a user license agreement. I will be grateful if somebody can send me a link to it; if one exists. Thank you very much ******************************************* Antonio Paredes USDA- Center for Veterinary Biologics Biometrics Unit 510 South 17th Street, Suite 104 Ames, IA 50010 (515) 232-5785 [[alternative

Hello everyone. Currently I am running R 2.2.1 (windows), and I will like to update to 2.3. I wanted to ask if it is possible to update without having to removed 2.2.1; or do I first need to delete 2.2.1? Thank you very much. Tony [[alternative HTML version deleted]]

Hello. Some months age an e-mail was posted in which a comparison between Glimmix and glm was discussed. I have not been able to find that e-mail on the R archive. Does anyone recall the date of the above e-mail? Thank you very much. ******************************************* Antonio Paredes USDA- Center for Veterinary Biologics Biometrics Unit 510 South 17th Street, Suite 104 Ames, IA 50010

Hello everyone. I would like to know if there is any R library to perform adaptive rejection sampling. Thanks in advance. ******************************************* Antonio Paredes USDA- Center for Veterinary Biologics Biometrics Unit 510 South 17th Street, Suite 104 Ames, IA 50010 (515) 232-5785 [[alternative HTML version deleted]]

Hello everyone. I want to write some likelihood functions to use with optim. For example AR-structures, I have written a couple of functions that appear to get the job done. But, since I am new to R, I wanted to ask if there are any references in this topic. Thanks in advance, ******************************************* Antonio Paredes USDA- Center for Veterinary Biologics Biometrics Unit

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.

Is there an implementation of the Cox-Snell residuals / Nelson-Aalen plot for goodness of fit? Or otherwise is there an appropriate Goodness of Fit diagnostic? Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

I am having difficulty loading a points shapefile (1600 records) I generated from ArcGIS as a PointsSpatialDataFrame using the maptools readShapePoints function. library(maptools) surveypts <- readShapePoints(system.file("C:/temp/survey.shp", package="maptools")[1] Error in getinfo.shape(filen) : Error opening SHP file I've tried numerous re-exports and renames of the

R-Experts: Does anyone know if there are R functions to perform the Freeman-Tukey double arcsine transformation and then backtransform it? Thanks, Brant Inman Mayo Clinic

Hi STATISTICA has a function called "Two-way joining" (see http://www.statsoft.com/TEXTBOOK/stcluan.html#twotwo) and the reference material states that this is based on the method as published by Hartigan (found this paper: http://www.jstor.org/pss/2284710 through wikipedia). What is the relationship (if any) between the "heatmap" function in R and this technique? Is there an

Hi, How do you folks handle really large queues (350+ simultaneous callers) in your Asterisk PBXes? We're going to be bringing in around 16 PRIs' worth of inbound callers, doing skills-based routing, and queuing them up for approximately 200 agents. What's the best way to handle all of these callers? We want to record the calls and we'll probably use the ramdisk method that has

Dear R Users, I suppose this is a school boy question, but here it is anyway. I'm trying to re-create the residuals for a poisson GLM with simulated data; x<-rpois(1000,5) model<-glm(x~1,poisson) my.resids<-(log(x)- summary(model)$coefficients[1]) plot(my.resids,residuals(model)) This shows that my calculated residuals (my.resids) are not the same as residuals(model). p 65 of

I found this paper on ANOVA on unequal error variance. Has this be incorporated to any R package? Is there any textbook that discuss the problem of ANOVA on unequal error variance in general? http://www.jstor.org/stable/2532947?cookieSet=1

I've noticed that the implementation of Kendall's Tau in R is O(N^2). The following reference describes how it can be done in O(N log N): A Computer Method for Calculating Kendall's Tau with Ungrouped Data William R. Knight Journal of the American Statistical Association, Vol. 61, No. 314, Part 1 (Jun., 1966), pp. 436-439 http://www.jstor.org/pss/2282833 I'm interested in

Hi, i'm newbie for this, but it's very interesting, but how i have to interpret the results if i get i.e. this results ? Is it correct - if the "Ratio of effect sd" is positiv than the Numerator effects are bigger , and the negative case vice-versa ? Ratio of effect standard deviations: 0.954 Log(sd ratio): -0.047 (se 0.828) Approximate 95% confidence

I would like to try a likelihood ratio test in place of waldtest. Ideally I'd like to provide two glm models, the second a submodel of the first, in the style of lrt (http://www.pik-potsdam.de/~hrust/tools/farismahelp/lrt.html). [lrt takes farimsa objects] Does anyone know of such a likelihood ratio test? Chris Elsaesser, PhD Principal Scientist, Machine Learning SPADAC Inc. 7921

Hello, While doing some enrichment tests using chisq.test() with simulated p-values, I noticed some strange behaviour. The computed p-value was extremely small, so I decided to dig a little deeper and debug chisq.test(). I noticed then that the simulated statistics returned by the following call tmp <- .Call(C_chisq_sim, sr, sc, B, E) were all the same, very small numbers. This, at first,