If you need an accessible version of this item please contact JSTOR User Support

AIC and Large Samples

I. A. Kieseppä
Philosophy of Science
Vol. 70, No. 5, Proceedings of the 2002 Biennial Meeting of The Philosophy of Science AssociationPart I: Contributed PapersEdited by Sandra D. Mitchell (December 2003), pp. 1265-1276
DOI: 10.1086/377406
Stable URL: http://www.jstor.org/stable/10.1086/377406
Page Count: 12
  • Download PDF
  • Cite this Item

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If you need an accessible version of this item please contact JSTOR User Support
AIC and Large Samples
Preview not available

Abstract

I discuss the behavior of the Akaike Information Criterion in the limit when the sample size grows. I show the falsity of the claim made recently by Stanley Mulaik in Philosophy of Science that AIC would not distinguish between saturated and other correct factor analytic models in this limit. I explain the meaning and demonstrate the validity of the familiar, more moderate criticism that AIC is not a consistent estimator of the number of parameters of the smallest correct model. I also give a short explanation why this feature of AIC is compatible with the motives for using it.

Page Thumbnails

  • Thumbnail: Page 
1
    1
  • Thumbnail: Page 
2
    2
  • Thumbnail: Page 
3
    3
  • Thumbnail: Page 
4
    4
  • Thumbnail: Page 
5
    5
  • Thumbnail: Page 
6
    6
  • Thumbnail: Page 
7
    7
  • Thumbnail: Page 
8
    8
  • Thumbnail: Page 
9
    9
  • Thumbnail: Page 
10
    10
  • Thumbnail: Page 
11
    11
  • Thumbnail: Page 
12
    12