Bayesian model selection for linear regression

Published 15 Dec 2015 in math.ST, stat.ME, and stat.TH | (1512.04823v1)

Abstract: In this note we introduce linear regression with basis functions in order to apply Bayesian model selection. The goal is to incorporate Occam's razor as provided by Bayes analysis in order to automatically pick the model optimally able to explain the data without overfitting.

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