BMS: Bayesian Model Averaging Library
Bayesian Model Averaging for linear models with a wide
choice of (customizable) priors. Built-in priorss 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 probabilitites, 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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Reverse dependencies: