Instrumentalism , Parsimony , and the Akaike Framework

  title={Instrumentalism , Parsimony , and the Akaike Framework},
  author={Elliott Sober},
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 sometimes test models whose truth values they already know, and then sometimes choose models that they know full well are false. Instrumentalism helps explain this pervasive feature of scientific practice, and Akaike’s framework provides instrumentalism with the epistemology it needs. Akaike’s criterion for… CONTINUE READING


Publications citing this paper.
Showing 1-10 of 20 extracted citations


Publications referenced by this paper.
Showing 1-10 of 20 references

2000b): “Key Concepts in Model Selection – Performance and Generality.

M. Forster
Feyerabend. London: Kluwer, • 2000
View 1 Excerpt

Instrumentalism Revisited.

E. Press. Sober
Molecular Systematics. Sunderland, MA: Sinauer, • 1998
View 1 Excerpt

Maximum Likelihood as an Alternative to Parsimony for Inferring Phylogeny Using Nucleotide Sequence Data.

P. Lewis
Molecular Systematics of Plants II. Boston: Kluwer, • 1998
View 2 Excerpts

Statistical Evidence – a Likelihood Paradigm

R. Royall
Akaike Information Criterion Statistics. New York: Springer. Schoener, • 1997
View 1 Excerpt

“ Phylogenetic Inference

D. Swofford, G. Olsen, P. Waddell, D. Hillis
View 2 Excerpts

Statistical SirensAllure of Nonparametrics

D. Johnson
View 1 Excerpt

Akaike’s estimated predictive accuracy as a quantity per datum, and so divided the right side of this equation by N, the number of data

Forster, Sober
View 3 Excerpts

Similar Papers

Loading similar papers…