Forster and Sober on the curve-fitting problem

Abstract
Forster and Sober present a solution to the curve-fitting problem based on Akaike's Theorem. Their analysis shows that the curve with the best epistemic credentials need not always be the curve that most closely fits the data. However, their solution does not, without further argument, avoid the two difficulties that are traditionally associated with the curve-fitting problem: that there are infinitely many equally good candidate-curves relative to any given set of data, and that these best candidates include curves with indefinitely many bumps
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Wang-Yen Lee (2013). Akaike's Theorem and Weak Predictivism in Science. Studies in History and Philosophy of Science Part A 44 (4):594-599.
Rhonda Martens (2009). Harmony and Simplicity: Aesthetic Virtues and the Rise of Testability. Studies in History and Philosophy of Science Part A 40 (3):258-266.
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