similar to: [SOLVED]looking for beta parameters

Hi, I'm new to R and I've run into a problem that I'm not really sure how to express properly in the language. I've got a data table that I've read from a file containing some simple information about the performance of 4 algorithms. The columns are the name of the algorithm, the problem instance and the resulting score on that problem (if it wasn't solved I mark that

Hi everyone. I have these data: probClass<-seq(0,0.9,0.1) prob1<-c(0.0070,0.0911,0.1973,0.2949,0.3936,0.5030,0.5985,0.6869,0.7820,0.8822) prob2<-c(0.0066,0.0791,0.2358,0.3478,0.3714,0.3860,0.6667,0.6400,0.7000,1.0000) # which I'm plotting as follows: plot(probClass,prob1,xlim=c(0,1),ylim=c(0,1),xaxs='i',yaxs='i',type="n") lines(probClass,prob1)

Hi, sorry this is so basic but I feel I'm so close to being able to sit quietly in a corner and do exactly what I planned from the start that I thought I would ask. All I want is to do is to run R (2.9.0 finally up and running!, struggling a bit with ESS but I'll get there) and use it to learn Bayesian analysis and some similar stuff. Actually I bought Peter Dalgaard's

Full_Name: Robert Peck Version: 2.8.1 OS: XP Home Submission from: (NULL) (71.168.114.196) There are some packages that I cannot install on my PC. Example: LearnBayes The following output is sent back: > utils:::menuInstallPkgs() trying URL 'http://www.ibiblio.org/pub/languages/R/CRAN/bin/windows/contrib/2.8/LearnBayes_2.0.zip' Content type 'application/zip' length 379068

I care a lot about R's speed. So I decided to give REvolution's R (http://revolution-computing.com/) a try, which bills itself as an optimized R. Note that I used the free version. My machine is a Intel core 2 duo under Windows XP professional. The code I run is in the end of this post. First, the regular R 1.9. It takes 2 minutes and 6 seconds, CPU usage 50% Next, REvolution's R.

Hello. I have yet to receive a response to my previous post, so I may have done a poor job asking the question. So, here is the general question: how can I run a run a multivariate (more than one non-independent, response variables) ordered probit regression model? I've had success doing this in the univariate case using the vglm() function in the VGAM package. For example:

I'm getting an error message when using the new version of sqldf, > library(sqldf) > str(kdv) 'data.frame': 71 obs. of 3 variables: $ dpss: num 0.117 0.144 0.164 0.166 0.165 ... $ npdp: num 0.1264 0.0325 0.0109 0.0033 0.0055 ... $ logk: num 1.12 1.29 1.41 1.41 1.42 ... > test=sqldf("select * from kdv") Error in get("fun", env = this, inherits =

First, I love R and am grateful to be using this free and extremely high quality software. Recently I have been comparing two algorithms and naturally I programmed in R first. It is so slow that I can almost feel its pain. So I decided to do a comparison with Java. To draw 500,0000 truncated normal, Java program takes 2 second and R takes 72 seconds. Not a computer science major, I find it hard

Hi, I've actually run R quite a bit in Windows. I've had a release 8.04 of Ubuntu running a laptop for 3 days now. After struggling for much of that time to install R, I finally figured out that Dell shipped with the sources.list obsolete or just plain wrong. So I finally got it installed last night (for some reason v2.6.2, not v2.9.x). This morning I was able to download and install

Dear R-users (and developers), I am looking for an efficient framework to carry out parameter estimations based on MCMC (optionally with specified priors). My goal is as follow: * take ANY R-function returning a likelihood-value (this function may itself call external programmes or other code!) * run a sampler that covers the multidimensional parameter space (thus creating a posterior

Dear R-Devel, I have had it in my mind for some time now that a Task View related to R and education might be a good thing. There are currently 19 Task Views, covering a broad spectrum of general topics for which R may be used. The homepage lists 64 books related to R, and several of them have accompanying packages on CRAN. There is a wiki and a host of contributed documentation. We also have a

Dear list, I'd like to test the null hypothesis of independence in a 2*2 contingency table in a Bayesian way. As far as I can see, this can be done by the function ctable in library LearnBayes. (More precisely, a Bayes factor can be computed.) Two questions: 1) Is there any other package/function than can be used for this in a more or less straightforward manner? 2) The ctable help page

Hello I wonder whether someone can tell me what I am doing wrong. Here is the code (from Bayesian Computation with R - Chapter 2.3.R) that I am trying to run #################################### # Section 2.3 Using a Discrete Prior #################################### graphics.off() # Close all graphics rm(list=ls()) # Clear all variables library(LearnBayes)

Hey, So I have a scatter plot and I am trying to plot a curve to fit the data based on a Holling Type III functional response. My function is this: nll2<-function(a,b) { conefun<-(a*DBH^2)/(b^2+DBH^2) nlls2<-dnbinom(x=cones ,size=DBH, mu=conefun,log=TRUE) -sum(nlls) } and my plot is this: plot (DBH,cones) DBH is on the x-axis and cones is on the y-axis. How do I get the curve

Hi, I am trying to run a generalized linear regression using a negative binomial error distribution. However, I want to use an overdispersion parameter that varies (dependent on the length of a stretch of road) so glm.nb will not do. >From what I've read I should be able to do this using GLM by specifying my own quasi family and describing the variance function using varfun, validmu,

Dear Ben, you answerd to Nancy Shackelford about Clarks 2Dt function. Since the thread ended just after your reply, I would like to ask, if you have an idea how to use this function in R I defined it the following way: function(x , p, u) { (p/(pi*u))*(1+(x^2/u))^(p+1) } and would like to fit this one to my obeservational data (count) [,1] [,2] [1,] 15 12 [2,] 45 13 [3,]

Hi, Please find the code and data following. Problem appears in lines 37 - 42 of the code. I am using R.2.13.0 on WinXP. Regards, Fayez PowerLawGraphsAblineQn.R? library('reshape') library(lattice) library(igraph) # to use power.law.fit function library(latticeExtra) # to use panel.lmlineq in loglog xyplot File2Open = "C:\\Documents and Settings\\All

Hi I'm trying to replicate Smith et al.'s (http://www.sciencemag.org/content/330/6008/1216.abstract) findings by fitting their Gompertz and logistic models to their data (given in their supplement). I'm doing this as I want to then apply the equations to my own data. Try as a might, I can't quite replicate them. Any thoughts why are much appreciated. I've tried contacting the

Hi there, I have been having trouble running negative binomial regression (glm.nb) using library MASS in R v2.15.0 on Mac OSX. I am running multiple models on the variables influencing the group size of damselfish in coral reefs (count data). For total group size and two of my species, glm.nb is working great to deal with overdispersion in my count data. For two of my species, I am getting a

I have been trying to create code to calculate the power for an adaptive design with a survival endpoint according to the method of Schafer and Muller ('Modification of the sample size and the schedule of interim analyses in survival trials based on interim inspections,' Stats in Med, 2001). This design allows for the sample size to be increased (if necessary) based on an interim look at