Bayesian Model Averaging Using Power-Expected-Posterior Priors
Dimitris Fouskakis () and
Ioannis Ntzoufras ()
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Dimitris Fouskakis: Statistics Lab, Department of Mathematics, National Technical University of Athens, Zografou Campus, 15780 Athens, Greece
Ioannis Ntzoufras: Computational and Bayesian Statistics Lab, Department of Statistics, Athens University of Economics and Business, 10434 Athens, Greece
Econometrics, 2020, vol. 8, issue 2, 1-15
This paper focuses on the Bayesian model average (BMA) using the power–expected– posterior prior in objective Bayesian variable selection under normal linear models. We derive a BMA point estimate of a predicted value, and present computation and evaluation strategies of the prediction accuracy. We compare the performance of our method with that of similar approaches in a simulated and a real data example from economics.
Keywords: Bayesian model averaging; Bayesian variable selection; expected–posterior priors; imaginary training samples; power–expected–posterior priors (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:8:y:2020:i:2:p:17-:d:356718
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