A New Algorithm in Bayesian Model Averaging in Regression Models

Abstract

We propose a new iterative algorithm, namely the model walking algorithm, to modify the widely used Occam’s window method in Bayesian model averaging procedure. It is verified, by simulation, that in the regression models, the proposed algorithm is much more efficient in terms of computing time and the selected candidate models. Moreover, it is not sensitive to the initial models.

Keywords:

• Ayesian model averaging
• Occam’s window
• Regression models

Mathematics Subject Classification:

• Primary 62F15
• 62J05
• 65C60
• Secondary 65C05