BMS: Bayesian Model Averaging Library

Bayesian Model Averaging for linear models with a wide choice of (customizable) priors. Built-in priors include coefficient priors (fixed, hyper-g and empirical priors), 5 kinds of model priors, moreover model sampling by enumeration or various MCMC approaches. Post-processing functions allow for inferring posterior inclusion and model probabilities, various moments, coefficient and predictive densities. Plotting functions available for posterior model size, MCMC convergence, predictive and coefficient densities, best models representation, BMA comparison. Also includes Bayesian normal-conjugate linear model with Zellner's g prior, and assorted methods.

Version:	0.3.5
Depends:	methods, stats, graphics, R (≥ 2.10)
Published:	2022-08-09
Author:	Martin Feldkircher and Stefan Zeugner and Paul Hofmarcher
Maintainer:	Stefan Zeugner <stefan.zeugner at ec.europa.eu>
License:	BSD_3_clause + file LICENSE
URL:	http://bms.zeugner.eu
NeedsCompilation:	no
Citation:	BMS citation info
Materials:	NEWS
In views:	Bayesian, Econometrics
CRAN checks:	BMS results

Documentation:

Reference manual:	BMS.pdf
Vignettes:	Bayesian Model Averaging with BMS

Downloads:

Package source:	BMS_0.3.5.tar.gz
Windows binaries:	r-devel: BMS_0.3.5.zip, r-release: BMS_0.3.5.zip, r-oldrel: BMS_0.3.5.zip
macOS binaries:	r-release (arm64): BMS_0.3.5.tgz, r-oldrel (arm64): BMS_0.3.5.tgz, r-release (x86_64): BMS_0.3.5.tgz, r-oldrel (x86_64): BMS_0.3.5.tgz
Old sources:	BMS archive

Linking:

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