Information Theory and an Extension of the Maximum Likelihood Principle View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1992

AUTHORS

Hirotogu Akaike

ABSTRACT

In this paper it is shown that the classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion. This observation shows an extension of the principle to provide answers to many practical problems of statistical model fitting. More... »

PAGES

610-624

References to SciGraph publications

  • 1969-12. Fitting autoregressive models for prediction in ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
  • 1970-12. Statistical predictor identification in ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
  • 1971-12. Autoregressive model fitting for control in ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
  • Book

    TITLE

    Breakthroughs in Statistics

    ISBN

    978-0-387-94037-3
    978-1-4612-0919-5

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-1-4612-0919-5_38

    DOI

    http://dx.doi.org/10.1007/978-1-4612-0919-5_38

    DIMENSIONS

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