Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions

Psychometrika

Volumn 52, Issue 3, 1987, Pages 345-370

  Bozdogan, Hamparsum ^a  

^a UNIVERSITY OF VIRGINIA   (United States)

Author keywords

AIC; Akaike's information criterion; asymptotic properties; CAIC; CAICF; model selection

Indexed keywords

EID: 34250108028     PISSN: 00333123     EISSN: 18600980     Source Type: Journal    
DOI: 10.1007/BF02294361     Document Type: Article

References (48)

1. Information theory and an extension of the maximum likelihood principle
2. A new look at the statistical model identification
3. Canonical correlation analysis of time series and the use of an information criterion
4. On entropy maximization principle
5. On newer statistical approaches to parameter estimation and structure determination
6. A Bayesian extension of the minimum AIC procedure of autogressive model fitting
7. Likelihood of a model and information criteria
8. Modern development of statistical methods
9. The choice of the degree of a polynomial regression as a multiple decision problem
10. A note on the generalized information criterion for choice of a model
11. Some properties of the order of an autoregressive model selected by a generalization of Akaike's FPE criterion
12. Über die Beziehung zwischen dem zweitin Hauptsatze der mechanischen Wärmetheorie und der Wahrscheinlichkeitsrechnung respective den Sätzen über das Wärmegleichgewicht
13. Filter-order selection in adaptive maximum likelihood estimation
14. The power of the likelihood ratio test
15. On the mathematical foundations of theoretical statistics
16. Remembrance of things past
17. The determination of the order of an autoregression
18. Information theory and statistical mechanics
19. Optimal choice of AR and MA parts in autoregressive moving average models
20. On the use of AIC for the detection of outliers
21. On information and sufficiency
22. The choice of variables in multiple regression (with discussion)
23. On the use and interpretation of certain test criteria for purposes of statistical inference
24. On the problem of the most efficient tests of statistical hypotheses
25. Data modeling using quantile and density-quantile functions
26. Order determination for a multivariate autoregression
27. Modeling by shortest data description
28. Estimating the dimension of a model
29. A theoretical view of the use of AIC
30. Admissible selection of an accurate and parsimonious normal linear regression model
31. Model selection criteria and model selection tests in regression models
32. Tests of statistical hypotheses concerning several parameters when the number of observations is large
33. Maximum likelihood estimation of misspecified models
34. On model selection and the arc sine laws