This chapter examines four solutions to the problem of many models, and finds some fault or limitation with all of them except the last. The first is the naïve empiricist view that best model is the one that best fits the data. The second is based on Popper’s falsificationism. The third approach is to compare models on the basis of some kind of trade off between fit and simplicity. The fourth is the most powerful: Cross validation testing.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
References found in this work BETA
No references found.
Citations of this work BETA
Mr. Fit, Mr. Simplicity and Mr. Scope: From Social Choice to Theory Choice.Michael Morreau - 2013 - Erkenntnis (S6):1-16.
Similar books and articles
Simplicity and Ontologies The Trade-Off Between Simplicity of Theories and Sophistication of Ontologies.Aaron Sloman - unknown
Statistical Model Selection Criteria and Bayesianism.I. A. Kieseppä - 2001 - Proceedings of the Philosophy of Science Association 2001 (3):S141 - S152.
Selection and the Unification of Science.Jay N. Eacker - 2001 - Behavioral and Brain Sciences 24 (3):535-536.
Bayes and Bust: Simplicity as a Problem for a Probabilist's Approach to Confirmation. [REVIEW]Malcolm R. Forster - 1995 - British Journal for the Philosophy of Science 46 (3):399-424.
Simplicity, Inference and Modeling: Keeping It Sophisticatedly Simple.Arnold Zellner, Hugo A. Keuzenkamp & Michael McAleer (eds.) - 2001 - Cambridge University Press.
Model Selection in Science: The Problem of Language Variance.MR Forster - 1999 - British Journal for the Philosophy of Science 50 (1):83-102.
Added to index2009-01-28
Total downloads45 ( #114,979 of 2,164,866 )
Recent downloads (6 months)2 ( #188,443 of 2,164,866 )
How can I increase my downloads?