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

Author:

Bozdogan Hamparsum

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,General Psychology

Reference48 articles.

1. Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov & B. F. Csaki (Eds.),Second International Symposium on Information Theory, (pp. 267–281). Academiai Kiado: Budapest.

2. Akaike, H. (1974). A new look at the statistical model identification.IEEE Transactions on Automatic Control, AC-19, 716–723.

3. Akaike, H. (1976). Canonical correlation analysis of time series and the use of an information criterion. In R. K. Mehra & D. G. Lainiotis (Eds.),System identification (pp. 27–96). New York: Academic Press.

4. Akaike, H. (1977). On entropy maximization principle. In P. R. Krishnaiah (Ed.),Proceedings of the Symposium on Applications of Statistics (pp. 27–47). Amsterdam: North-Holland.

5. Akaike, H. (1978). On newer statistical approaches to parameter estimation and structure determination.International Federation of Automatic Control, 3, 1877–1884.

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