A comparison of Bayesian variable selection approaches for linear models
Bayesian variable selection approaches are more powerful in discriminating among models regardless of whether these models under investigation are hierarchical or not. Although Bayesian approaches require complex computation, use of theMarkov Chain Monte Carlo (MCMC) methods, such as, Gibbs sampler...
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2014
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| Online Access: | http://cardinalscholar.bsu.edu/handle/123456789/198141 http://liblink.bsu.edu/uhtbin/catkey/1749597 |