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
Boosting distributional copula regression.
Sign Up to like & getrecommendations! Published in 2022 at "Biometrics"
DOI: 10.1111/biom.13765
Abstract: Capturing complex dependence structures between outcome variables (e.g., study endpoints) is of high relevance in contemporary biomedical data problems and medical research. Distributional copula regression provides a flexible tool to model the joint distribution of… read more here.
Keywords: regression; copula; boosting distributional; copula regression ... See more keywords
Gaussian Copula Regression in R
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Statistical Software"
DOI: 10.18637/jss.v077.i08
Abstract: This article describes the R package gcmr for fitting Gaussian copula marginal regression models. The Gaussian copula provides a mathematically convenient framework to handle various forms of dependence in regression models arising, for example, in… read more here.
Keywords: package; copula regression; gaussian copula; regression ... See more keywords