search for: bayesians

Hi all, May i know does R has packages or code to run "Bayesian Relative Survival Analysis"? I have look through Bayesian Survival Analysis(2001) by Joseph George Ibrahim<http://www.google.com/search?tbo=p&tbm=bks&q=inauthor:%22Joseph+George+Ibrahim%22>, Ming-Hui Chen<http://www.google.com/search?tbo=p&tbm=bks&q=inauthor:%22Ming-Hui+Chen%22>, Debajyoti

Dear all, I am trying to learn Bayesian inference and Bayesian data analysis, I am new in the field. Would any experts on the list recommend any good sites or materials for beginners? My approach is to learn and understand the theory first, then program on my own using R, though I see there are already packages. appreciate any help, thanks in advance!

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

Hi everyone, I am wondering if there exists a stepwise regression function for the Bayesian regression model. I tried googling, but I couldn't find anything. I know "step" function exists for regular stepwise regression, but nothing for Bayes. Thanks -- View this message in context: http://www.nabble.com/Bayesian-regression-stepwise-function--tp26013725p26013725.html Sent from

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 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,

I'm just starting to learn to use R, and although I'm seeing lots of functions aimed at doing orthodox statistical analyses, I don't see the same for Bayesian analyses. What support does R have for Bayesian statistics?

Looking for help with a project for the US Navy, requires knowledge of Bayesian Statistics, Bayesian Networks and Survival Analysis. Please respond with CV. Thanks. -- David Katz www.davidkatzconsulting.com [[alternative HTML version deleted]]

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.

Hi all, I would like to start to use R's MCMC abilities to compute answers in Bayesian statistics. I don't have any specific problems in mind yet, but I would like to be able to compute/sample posterior probabilities for low-dimensional custom models, as well as handle "standard" Bayesian cases like linear regression and hierarchical models. R clearly has a lot of abilities in

I am trying to calculate Bayesian Credible Intervals for a proportion (disease prevalence values to be more specific) and am having trouble using R to do this. I am working with ncredint() function but have not had success with it. Please help! Example: Positive samples = 3 Total sampled = 10 Prevalence = 0.3 pvec <- seq(1,10,by=1) npost = dbinom(pvec,10,prob=0.3, log=FALSE) ncredint(pvec,

HeLLo, I'm new in R, I would like to use it for diagnostics with bayesian network, I want to know how can I calculate inference and if can I enter my probability tables like logical or arithmetic equation, Thanks. -- View this message in context: http://r.789695.n4.nabble.com/Bayesian-network-tp4662059.html Sent from the R help mailing list archive at Nabble.com.

Dear Oscar,   Thanks for your help.It's so nice of you to explain this package to me.   Best Regards,   James LAN 发件人： Oscar Rueda [via R] <ml-node+s789695n4431468h14@n4.nabble.com> 收件人： monkeylan <lanjinchi@yahoo.com.cn> 发送日期： 2012年2月29日, 星期三, 下午 9:21 主题: Re: Bayesian Hidden Markov Models Dear James, The distances are normalized between zero and 1, so in your case all of

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

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:

I apologize if this question is not completely appropriate for this list. I have been using SAS for a while and am now in the process of learning some C and R as a part of my graduate studies. All of the statistical packages I have used generally yield p-values as a default output to standard procedures. This week I have been reading "Testing Precise Hypotheses" by J.O. Berger

Hello, I'm interested in doing Bayesian kriging using R. I see that the package geoR has a function that will allow one to do this (krige.bayes). However, my data are not in the form of points, but rather they are blocks that represent spatial averages (i.e., the number of fishing hooks per month in a given lat x long square). I am therefore interested in treating the data as

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 useRs, French reading people among you might be interested by the following book: Noel, Y. (2013). Psychologie statistique avec R [Statistical psychology with R, in French], coll. PratiqueR, Paris: Springer. http://www.springer.com/psychology/book/978-2-8178-0424-8 This book provides a detailed presentation of all basics of statistical inference for psychologists, both in a fisherian

Hi Friends, I'm trying to model the consumer decisions (Click-Through Rate and Conversion) in Search Engine Advertising using a hierarchical Bayesian binary logit. The input data is the weekly CTRs and Avg. Position for each search keyword. CTR is modeled as (for each keyword i and week j): Pij = exp(C + Bi x Positionij + A1 x Lengthi + A2 x Brandi + A3 x ProductSpecifici) / [1 + exp(C +