The Annals of Statistics
- Ann. Statist.
- Volume 6, Number 2 (1978), 461-464.
Estimating the Dimension of a Model
Abstract
The problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion. These terms are a valid large-sample criterion beyond the Bayesian context, since they do not depend on the a priori distribution.
Article information
Source
Ann. Statist., Volume 6, Number 2 (1978), 461-464.
Dates
First available in Project Euclid: 12 April 2007
Permanent link to this document
https://projecteuclid.org/euclid.aos/1176344136
Digital Object Identifier
doi:10.1214/aos/1176344136
Mathematical Reviews number (MathSciNet)
MR468014
Zentralblatt MATH identifier
0379.62005
JSTOR
links.jstor.org
Subjects
Primary: 62F99: None of the above, but in this section
Secondary: 62J99: None of the above, but in this section
Keywords
Dimension Akaike information criterion asymptotics
Citation
Schwarz, Gideon. Estimating the Dimension of a Model. Ann. Statist. 6 (1978), no. 2, 461--464. doi:10.1214/aos/1176344136. https://projecteuclid.org/euclid.aos/1176344136
