Using the EM algorithm for Bayesian variable selection in logistic regression models with related covariates
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2017.1398255
Abstract: ABSTRACT We develop a Bayesian variable selection method for logistic regression models that can simultaneously accommodate qualitative covariates and interaction terms under various heredity constraints. We use expectation-maximization variable selection (EMVS) with a deterministic annealing… read more here.
Keywords: logistic regression; regression models; bayesian variable; heredity ... See more keywords
Bayesian Variable Selection for Gaussian Copula Regression Models
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Computational and Graphical Statistics"
DOI: 10.1080/10618600.2020.1840997
Abstract: Abstract We develop a novel Bayesian method to select important predictors in regression models with multiple responses of diverse types. A sparse Gaussian copula regression model is used to account for the multivariate dependencies between… read more here.
Keywords: regression; regression models; bayesian variable; gaussian copula ... See more keywords
Identifying the source of food-borne disease outbreaks: An application of Bayesian variable selection
Sign Up to like & getrecommendations! Published in 2019 at "Statistical Methods in Medical Research"
DOI: 10.1177/0962280217747311
Abstract: Early identification of contaminated food products is crucial in reducing health burdens of food-borne disease outbreaks. Analytic case-control studies are primarily used in this identification stage by comparing exposures in cases and controls using logistic… read more here.
Keywords: disease outbreaks; bayesian variable; borne disease; food borne ... See more keywords