Bayesian model selection for linear regression

2015/12/15 by Miguel de Benito Delgado, Philipp Wacker, Delgado, Miguel de Benito +1
Engineering · #62F15 #62J05 #FOS: Computer and information sciences #FOS: Mathematics #Fault Detection and Control Systems #Methodology (stat.ME) #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.1512.04823

openalex publication_date 2015/12/15 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28

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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