similar to: Help with Bayesian Logistic Regression

Dear all, I want to build a text classification model with about 85.000 features (variables) on about 10.000 observations (words that have been manually classified). I want to use multivariate logistic regression (known also as maximum entropy) with Gaussian priors. So in essence it is Bayesian logistic regression. Is there R package which is suitable for such model and problem size? thanks,

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){

Hi all. Are there any R functions around that do quick logistic regression with a Gaussian prior distribution on the coefficients? I just want posterior mode, not MCMC. (I'm using it as a step within an iterative imputation algorithm.) This isn't hard to do: each step of a glm iteration simply linearizes the derivative of the log-likelihood, and, at this point, essentially no

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.

Sincerely, Jeffrey Todd Lins Executive Director Quantitative Analysis Saxo Bank A/S (Sent from my BlackBerry) ----- Original Message ----- From: r-sig-finance-bounces at stat.math.ethz.ch <r-sig-finance-bounces at stat.math.ethz.ch> To: r-help <R-help at stat.math.ethz.ch>; r-sig-finance at stat.math.ethz.ch <r-sig-finance at stat.math.ethz.ch> Sent: Wed Apr 02 06:49:54 2008

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:

Hello R users! I've been experimenting with lmer to estimate a mixed model with a dichotomous dependent variable. The goal is to fit a hierarchical model in which we compare the effect of individual and city-level variables. I've run up against a conceptual problem that I expect one of you can clear up for me. The question is about random effects in the context of a model fit with a

Dear R users, I am pleased to announce the release of a new packaged called `bcrm? (version 0.1), now available on CRAN. The package implements a wide range of Bayesian continuous reassessment method (CRM) designs to be used in Phase I dose-escalation trials. The package is fully documented and highlights include ? A choice of 1-parameter working models or the 2-parameter logistic model.

Dear R users, I am pleased to announce the release of a new packaged called `bcrm? (version 0.1), now available on CRAN. The package implements a wide range of Bayesian continuous reassessment method (CRM) designs to be used in Phase I dose-escalation trials. The package is fully documented and highlights include ? A choice of 1-parameter working models or the 2-parameter logistic model.

Hi Everybody, A new package called ``Bayesian Prediction with High-order Interactions'' is available from CRAN. The description of this package is as follows" "This R package is used in two situations. The first is to predict the next outcome based on the previous states of a discrete sequence. The second is to classify a discrete response based on a number of discreate

Hi Everybody, A new package called ``Bayesian Prediction with High-order Interactions'' is available from CRAN. The description of this package is as follows" "This R package is used in two situations. The first is to predict the next outcome based on the previous states of a discrete sequence. The second is to classify a discrete response based on a number of discreate

I am working with a logistic-normal model (i.e, GLMM with random intercept model) by Bayesian method. BUt I met some difficulities for programming by R. Is there anyone have experience of this model or the R code I can refer as example? Thanks for your help. Syl

Hi, I would like to apply the L-BFGS optimization algorithm to compute the MLE of a multilevel multinomial Logistic Regression. The likelihood formula for this model has as one of the summands the formula for computing the likelihood of an ordinary (single-level) multinomial logit regression. So I would basically need the R implementation for this formula. The L-BFGS algorithm also requires

oops, Forgot to cc to the list. Regards, Mike -----Original Message----- From: dr mike [mailto:dr.mike at ntlworld.com] Sent: 24 February 2005 19:21 To: 'Spencer Graves' Subject: RE: [R] Bayesian stepwise (was: Forward Stepwise regression based onpartial F test) Spencer, Obviously the problem is one of supersaturation. In view of that, are you aware of the following? A Two-Stage

Hi All: Recently I am researching my dissertation about the quantile model selection by bayesian approach. I have the dependent variable(return) and 16 independent variables and I need to select the best variable for each quantile of return. And the method I used is the bayesian approach, which is based on calculating the posterior distibution of model identifier. In other words, I need to obtain

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

sir, i am trying to install r package Bayesian quantile regression but i am facing with following problem which says forPlease select a CRAN mirror for use in this session --- Warning: unable to access index for repository http://cran.cnr.Berkeley.edu/bin/windows/contrib/2.6 Warning: unable to access index for repository http://www.stats.ox.ac.uk/pub/RWin/bin/windows/contrib/2.6 Error in

Christoph Lehman had problems with seperated data in two-class logistic regression. One useful little trick is to penalize the logistic regression using a quadratic penalty on the coefficients. I am sure there are functions in the R contributed libraries to do this; otherwise it is easy to achieve via IRLS using ridge regressions. Then even though the data are separated, the penalized

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,