similar to: How To Specify An Improper Uniform Prior (Bayesian Analysis)

Dear list members, Apologies for cross-posting. Please, find below the information of two statistical courses with R: 1) Statistical Analysis with R 2) Bayesian Data Analysis with R and WinBUGS If you have any question don't hesitate to contact me. Best regards, Pablo ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ *Two days course in: Statistical Analysis with R *Where:

Dear list members, Best greetings and apologies for cross-posting. There are available places for the course: "Bayesian Data Analysis with R and WinBUGS", please find the description of the course below. If you have any question don't hesitate to contact me. Best regards, Pablo ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ *Three days course in: Bayesian Data

Apologies for cross-posting. Places are available in the following course: "Introduction to Bayesian Data Analysis using WinBUGS and R" Best Regards, Pablo ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Course: Introduction to Bayesian Data Analysis using WinBUGS and R Where: Linux Hotel, Essen-Horst, Germany

Dear list members, Apologies for cross-posting. Please, find below the information of an introductory Bayesian Data Analysis course with WinBUGS and R. If you have any question don't hesitate to contact me. Best regards, Pablo ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Course: Introduction to Bayesian Data Analysis using WinBUGS and R Where: Linux Hotel, Essen-Horst,

Hi R User, I was trying to use R for WINBUGS using following model and data (example), but I am new with WINBUGS and don't know how we perform the analysis. I wonder whether I can run the following the example data and Winbugs Model in R. Your help will be highly appreciated. Sincerely, SN PANDIT === library(R2WinBUGS) #Model model{ #likelihood for(i in 1:N){ a1[i] ~ dnorm(a11[i],tau)

Hi R User, I was trying to use R for WINBUGS using following model and data (example), but I am new with WINBUGS and don't know how we perform the analysis. I wonder whether I can run the following the example data and Winbugs Model in R. Your help will be highly appreciated. Sincerely, SN PANDIT === library(R2WinBUGS) #Model model{ #likelihood for(i in 1:N){ a1[i] ~ dnorm(a11[i],tau)

Workshop on Bayesian methods and WinBUGS *************************************** A two-day workshop on Bayesian methods is being held on Friday 3 - Saturday 4 February 2012 at the University of Sydney. This course is suitable for graduate students, academics, researchers and professionals who wish to introduce themselves in the application of Bayesian methods and the use of WinBUGS software.

Dear all, I am trying to use the logistic regression with MCMClogit (package: MCMCpack/Coda) and I want to put a beta prior on the parameters, but it's giving me error message (please see output below) no matter what shape 1 or 2 I use. It works perfect with the cauchy or normal priors. Do you know if there is a catch there somewhere? Thanks logpriorfun <- function(beta,shape1,shape2){

Dear R-help, I'm using the R2WinBUGS package and getting an error message: Error in file(file, "r") : unable to open connection In addition: Warning message: cannot open file 'codaIndex.txt', reason 'No such file or directory' I'm using R 2.2.1 and WinBUGS 1.4.1 on a windows machine (XP). My R code and WinBUGS code is given below.

Dear R-help, I'm using the R2WinBUGS package and getting an error message: Error in file(file, "r") : unable to open connection In addition: Warning message: cannot open file 'codaIndex.txt', reason 'No such file or directory' I'm using R 2.2.1 and WinBUGS 1.4.1 on a windows machine (XP). My R code and WinBUGS code is

I am using a binomial mixture model to estimate abundance (N) and detection probability (p) using simulated count data: -Each site has a simulated abundance that follow a Poisson distribution with lambda = 5 -There are 200 simulated sampled sites -3 repeated counts at each site - only 50 percent of the animals are counted during each count (i.e, detection probability p =0.5, see codes) We removed

Hi all! I'm new to this forum so please excuse me if I don't conform perfectly to the protocols on this board! I'm trying to get an estimate of true prevalence based upon results from an imperfect test. I have various estimates of se/sp which could inform my priors (at least upper and lower limits even if with a uniform distribution) and found the following code on this website..

Hi. I am trying to analyze with BRugs the Box-Tiao variance components example in WinBUGS. The output from BRugs, mean sd MC_error val2.5pc median val97.5pc start sample sigma2.btw 681.9 1161 10.89 0.7016 253.8 4232 25001 100000 sigma2.with 4266.0 1246 4.92 2480.0000 4057.0 7262 25001 100000 doesn't match the output from WinBUGS, node mean

Dear friends, Over the past weeks, I have been asking a lot of questions about how to use R in Bayesian analysis. I am brand new to R, but I am very pleased with it. I started with winbugs but I found winbugs to be a limited software, not bad but has several limitations. By contrast, R allows the analyst to tackle any problem with a huge set of tools for any kind of analysis. I love R. In

I am an economist who decided it's high time that I learned some Bayesian statistics. I am following An Introduction to Modern Bayesian Econometrics by T. Lancaster. The book recommends using BUGS, but I wonder if there are any alternatives which are free software and fully integrated to R (which I have been using for more than two years for numerical computations.) I would like to learn

Dear R-users, I would like to announce the release of the new package JMbayes available from CRAN (http://CRAN.R-project.org/package=JMbayes). This package fits shared parameter models for the joint modeling of normal longitudinal responses and event times under a Bayesian approach using JAGS, WinBUGS or OpenBUGS. The package has a single model-fitting function called jointModelBayes(),

Dear R-users, I would like to announce the release of the new package JMbayes available from CRAN (http://CRAN.R-project.org/package=JMbayes). This package fits shared parameter models for the joint modeling of normal longitudinal responses and event times under a Bayesian approach using JAGS, WinBUGS or OpenBUGS. The package has a single model-fitting function called jointModelBayes(),

I'm trying to understand how a latent state matrix is updated by the MCMC iterations in a WinBUGS model, using the package R2WinBUGS and an example from Kery and Schaub's (2012) book, "Bayesian Population Analysis Using WinBUGS". The example I'm using is 7.3.1. from a chapter on the Cormack-Jolly-Seber model. Some excerpted code is included at the end of this message;

Hi all, I observed that the 'link' between R and BUGS (winBugs/linBugs) has totally disappeared. I'm wondering what package can be use to run bayesian models specified using the BUGS language in R (specifically under Linux). Is there any other option besides JAGS ? Thanks ----------------------------------------- Stay ahead of the information curve. Receive EDA news and jobs on

Hello, for a frequency modelling problem I want to combine expert knowledge with incoming real-life data (which is not available up to now). The frequency has to be modelled with a poisson distribution. The parameter lambda has to be normal distributed (for certain reasons we did not NOT choose gamma althoug it would make everything easier). I've started with the subsequent two functions to