Beauchamp. Bayesian variable selection in linear regression. Journal of the American Statistical Association, 83(404):1023-1032, 1988.Mitchell TJ, Beauchamp JJ (1988). "Bayesian Variable Selection in Linear Regression." Jour- nal of the American Statistical Association, 83(404), 1023-1032. doi:...
Performance of Variable Selection Methods in Regression using Variations of the Bayesian Information Criterion, LAUR05-6324, submitted for publication - Burr, Fry, et al. - 2005 () Citation Context ..., and then Bayesian Model Averaging (BMA) [40] can be used to estimate the probability that...
This article is concerned with the selection of subsets of predictor variables in a linear regression model for the prediction of a dependent variable. It is based on a Bayesian approach, intended to be as objective as possible. A probability distribution is first assigned to the dependent variabl...
An objective Bayesian procedure for variable selection in regression - Girón, Moreno, et al. - 2006Giron, F.J., Moreno, E. and Martinez, M.L. (2005b). An objective Bayesian procedure for variable selection in regression. Technical Report. University of Granada....
Komaki. Determinantal point process priors for Bayesian variable selection in linear regression. Statist. Sinica, 26(1):97-117, 2016.K. Mutsuki and K. Fumiyasu. Determinantal point process priors for Bayesian variable selection in linear regression. Statistica Sinica, 26:97-117, 2016....
Despite the abundance of methods for variable selection and accommodating spatial structure in regression models, there is little precedent for incorporating spatial dependence in covariate inclusion probabilities for regionally varying regression models. The lone existing approach is limited by difficult ...
In this work we introduce a new model space prior for Bayesian variable selection in linear regression. This prior is designed based on a recursive constructive procedure that randomly generates models by including variables in a stagewise fashion. We provide a recipe for carrying out Bayesian variab...
Recently, Bayesian spike and slab priors have been applied to predictive modeling and variable selection in large-scale genomic studies: see [37] for a simple review. Nevertheless, model selection has never been considered in a two-part regression model with latent variables. In this study, we ...
Run pkgdown::build_site() to build the pkgdown site. To format R codes in the R folder, for i in `ls R/*.R`; do bash inst/misc/format_r_code.sh $i; doneAbout A new model and algorithm for multivariate Bayesian variable selection regression. stephenslab.github.io/mvsusieR Resour...
Consider Bayesian variable selection in normal linear regression models based on Zellner’s \(g\)-prior. We study theoretical properties of this method when the sample size \(n\) grows and consider the cases when the number of regressors, \(p\) is fixed and when it grows with \(n\). ...