Information Theory and an Extension of the Maximum Likelihood Principle
H. Akaike. Selected Papers of Hirotugu Akaike, Springer New York, DOI: 10.1007/978-1-4612-1694-0\_15.(1998)
Zusammenfassung
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.
%0 Book Section
%1 akaike_information_1998
%A Akaike, Hirotogu
%B Selected Papers of Hirotugu Akaike
%D 1998
%E Parzen, Emanuel
%E Tanabe, Kunio
%E Kitagawa, Genshiro
%I Springer New York
%K Chemistry Computer Earth Engineering, Physics, Probability Processes, Science, Sciences Statistics Stochastic Theory and for
%P 199--213
%T Information Theory and an Extension of the Maximum Likelihood Principle
%U http://link.springer.com/chapter/10.1007/978-1-4612-1694-0_15
%X 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.
%@ 978-1-4612-7248-9 978-1-4612-1694-0