BayesSUR: Bayesian Seemingly Unrelated Regression

Bayesian seemingly unrelated regression with general variable selection and dense/sparse covariance matrix. The sparse seemingly unrelated regression is described in Banterle et al. (2018) <doi:10.1101/467019>.

Version: 1.2-3
Depends: R (≥ 3.5.0)
Imports: Rcpp, xml2, igraph, Matrix, tikzDevice, stats, utils, grDevices, graphics
LinkingTo: Rcpp, RcppArmadillo (≥ 0.9.000)
Suggests: R.rsp, BDgraph, data.table, plyr, scrime
Published: 2020-10-14
Author: Marco Banterle [aut], Zhi Zhao [aut, cre], Leonardo Bottolo [ctb], Sylvia Richardson [ctb], Waldir Leoncio [ctb], Alex Lewin [aut], Manuela Zucknick [ctb]
Maintainer: Zhi Zhao <zhi.zhao at>
License: MIT + file LICENSE
Copyright: The C++ files pugixml.cpp, pugixml.hpp and pugiconfig.hpp are Copyright (C) 2006-2018 by Arseny Kapoulkine ( and Copyright (C) 2003 by Kristen Wegner ( The R function vertical.image.legend() has Copyright (C) 2013 by Jenise Swall (
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: BayesSUR results


Reference manual: BayesSUR.pdf
Vignettes: BayesSUR: An R package for high-dimensional multivariate Bayesian variable and covariance selection in linear regression
Package source: BayesSUR_1.2-3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: BayesSUR_1.2-3.tgz, r-oldrel: BayesSUR_1.2-3.tgz
Old sources: BayesSUR archive


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