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BMS toolbox for Matlab: Bayesian Model Averaging (BMA) 1.0

  Date Added: August 08, 2013  |  Visits: 273

BMS toolbox for Matlab: Bayesian Model Averaging (BMA)

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Bayesian Model Averaging for linear models under Zellner's g prior. Options include: fixed (BRIC, UIP, ...) and flexible g priors (Empirical Bayes, hyper-g), 5 kinds of model prior concepts, and model sampling via model enumeration or MCMC samplers (Metropolis-Hastings plain or reversible jump). Post-processing allows for inference according to different concepts (likelihood vs MCMC-based) and for plotting (posterior model size and coefficient densities, best models, model convergence, BMA comparison).Needs the R D-COM interface or RAndFriends installed.Works for Matlab 6.5 and laterFor more details see:http://bms.zeugner.eu/matlab/

Requirements: No special requirements
Platforms: Matlab
Keyword: Coefficient Inference Likelihood Mcmcbased Plotting Posterior Postprocessing
Users rating: 0/10

License: Shareware Size: 61.44 KB
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