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Inherent Complexity: A Problem for Statistical Model Evaluation

Published online by Cambridge University Press:  01 January 2022

Jan-Willem Romeijn
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Abstract

This article investigates a problem for statistical model evaluation, in particular for curve fitting: by employing a different family of curves we can fit any scatter plot almost perfectly at apparently minor cost in terms of model complexity. The problem is resolved by an appeal to prior probabilities. This leads to some general lessons about how to approach model evaluation.

Information

Type
Evidence and Inference
Information
Philosophy of Science , Volume 84 , Issue 5 , December 2017 , pp. 797 - 809
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

The author wishes to thank Aidan Lyon, Elliott Sober, Jan Sprenger, and Tom Sterkenburg, as well as audiences in Santiago de Compostella, Padova, Helsinki, Gent, and Groningen.

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