R package 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, flexible and hyper-g 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.
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References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Leopoldo Catania; Nima Nonejad: Dynamic Model Averaging for Practitioners in Economics and Finance: The eDMA Package (2018) not zbMATH
- Marcin Błażejowski; Jacek Kwiatkowski: Bayesian Model Averaging and Jointness Measures for gretl (2015) not zbMATH
- Stefan Zeugner; Martin Feldkircher: Bayesian Model Averaging Employing Fixed and Flexible Priors: The BMS Package for R (2015) not zbMATH