The curve fitting problem: A bayesian rejoinder

Philosophy of Science 66 (3):402 (1999)
Abstract
In the curve fitting problem two conflicting desiderata, simplicity and goodness-of-fit pull in opposite directions. To solve this problem, two proposals, the first one based on Bayes's theorem criterion (BTC) and the second one advocated by Forster and Sober based on Akaike's Information Criterion (AIC) are discussed. We show that AIC, which is frequentist in spirit, is logically equivalent to BTC, provided that a suitable choice of priors is made. We evaluate the charges against Bayesianism and contend that AIC approach has shortcomings. We also discuss the relationship between Schwarz's Bayesian Information Criterion and BTC
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Citations of this work BETA
Prasanta S. Bandyopadhyay & Gordon Brittan (2010). Two Dogmas of Strong Objective Bayesianism. International Studies in the Philosophy of Science 24 (1):45 – 65.
Jan Sprenger (2013). The Role of Bayesian Philosophy Within Bayesian Model Selection. European Journal for Philosophy of Science 3 (1):101-114.
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