Methods and Tools for Bayesian Variable Selection and Model Averaging in Normal Linear Regression |
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| Authors: | Anabel Forte Gonzalo Garcia‐Donato Mark Steel |
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| Affiliation: | 1. Department of Statistics and Operations research, University of Valencia, València, Spain;2. Department of Economics and Finance and Instituto de Desarrollo Regional, University of Castilla‐La Mancha, Ciudad Real, Spain;3. Department of Statistics, University of Warwick, Coventry, UK |
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| Abstract: | In this paper, we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior elicitation, summaries of the posterior distribution and computational strategies. We then examine and compare various publicly available R‐packages, summarizing and explaining the differences between packages and giving recommendations for applied users. We find that all packages reviewed (can) lead to very similar results, but there are potentially important differences in flexibility and efficiency of the packages. |
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