similar to: Bayesian data analysis recommendations

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

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?

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

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.

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,

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]]

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

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 +

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

Deal R Users, I'm trying to find out how can I compute probabilities on a Bayesian Network using R. The Bayesian Network I modelled is shown at http://www.dsr.inpe.br/~mello/1727/BNgrapmodel.png and I'd like to know how can I proceed (commands on R) to answer questions like: (1) what is the probability of S=T given C=T, L=T, R=F, H=F and D=F; or (2) what is the probability of S=T

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

The article on BMA (Bayesian model averaging) presents most valuable tools for model selection, but I find one detail confusing in Example 1. In page 4 of RNews 5/2, second paragraph says that the probability of Time variable not being in the model is 0.445. It seems to me that the figure should be 1 - 0.445 = 0.555, because p!=0.445 is the prob. of Time variable being in the model. The plot in

Hello, Is there a function in R by which one can run AR model with Bayesian Information Criteria (BIC)? To my knowledge, functions ar and ar.ols could select the order only by AIC. Thanks, Miao [[alternative HTML version deleted]]

Hi, I am interested in using a bayesian network as a predictor (machine learning); however, I can't get any of the implementations (deal, nblearn) to learn & predict stuff. Shouldn't there also be probabilites for each node after the learning phase, how can I access these? Cheers, Stephan -- View this message in context:

Hello: I have looked at the bnlearn and deal packages for infering bayesian network. Can anyone suggest any other suitable package for constructing bayesian gene regulatory network using gene expression data? Thanks! John [[alternative HTML version deleted]]

Hello, I would like to use Bayesian Networks with R. I have already installed the package called deal which has succefully unpacked (package 'deal' successfully unpacked and MD5 sums checked) . But when I try to write " <- network (df) I have that kind of error message (be low)! rats <- network(rats.df) Error: couldn't find function "network" Thank u for your

Hi R, What package of R can I use for Bayesian States Space Modeling? And any other supporting packages? Thanks in advance, Shubha [[alternative HTML version deleted]]

Dear Members i'm trying to access different packages used for Bayesian analysis, but failed to integrate after making the likelihood of the model the model like this a= exp(b)/summation(exp(b)) where 'b' = half of the natural log of 'a' please If some one knows about this type of integration for posterior distribution then pleae inform me SYED ADIL HUSSAIN MPHIL SCHOLER QAU,