David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Proceedings of the Philosophy of Science Association 2002 (3):S112-S123 (2002)
Akaike’s framework for thinking about model selection in terms of the goal of predictive accuracy and his criterion for model selection have important philosophical implications. Scientists often test models whose truth values they already know, and they often decline to reject models that they know full well are false. Instrumentalism helps explain this pervasive feature of scientific practice, and Akaike’s framework helps provide instrumentalism with the epistemology it needs. Akaike’s criterion for model selection also throws light on the role of parsimony considerations in hypothesis evaluation. I explain the basic ideas behind Akaike’s framework and criterion; several biological examples, including the use of maximum likelihood methods in phylogenetic inference, are considered.
|Keywords||No keywords specified (fix it)|
No categories specified
(categorize this paper)
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
John R. Welch (2013). New Tools for Theory Choice and Theory Diagosis. Studies in History and Philosophy of Science 44 (3):318-329.
Prasanta S. Bandyopadhyay, Mark Greenwood, Gordon Brittan Jr & Ken A. Aho (forthcoming). Empiricism and/or Instrumentalism? Erkenntnis:1-23.
Similar books and articles
Olivier Rieppel (2007). Parsimony, Likelihood, and Instrumentalism in Systematics. Biology and Philosophy 22 (1):141-144.
Gregory M. Mikkelson (2006). Realism Versus Instrumentalism in a New Statistical Framework. Philosophy of Science 73 (4):440-447.
I. A. Kieseppä (2003). AIC and Large Samples. Philosophy of Science 70 (5):1265-1276.
I. A. Kieseppä (2003). AICand Large Samples. Philosophy of Science 70 (5):1265-1276.
I. Kieseppa (1997). Akaike Information Criterion, Curve-Fitting, and the Philosophical Problem of Simplicity. British Journal for the Philosophy of Science 48 (1):21-48.
Wayne C. Myrvold & William L. Harper (2002). Model Selection, Simplicity, and Scientific Inference. Proceedings of the Philosophy of Science Association 2002 (3):S135-S149.
Joel D. Velasco & Elliott Sober (2010). Testing for Treeness: Lateral Gene Transfer, Phylogenetic Inference, and Model Selection. Biology and Philosophy 25 (4):675-687.
I. A. Kieseppä (1997). Akaike Information Criterion, Curve-Fitting, and the Philosophical Problem of Simplicity. British Journal for the Philosophy of Science 48 (1):21-48.
Elliott Sober (1996). Parsimony and Predictive Equivalence. Erkenntnis 44 (2):167 - 197.
Added to index2009-01-28
Total downloads30 ( #62,265 of 1,101,838 )
Recent downloads (6 months)1 ( #306,556 of 1,101,838 )
How can I increase my downloads?