Introduction to Akaike (1973) Information Theory and an Extension of the Maximum Likelihood Principle In Breakthroughs in Statistics (1992), pp. 599-609, doi:10.1007/978-1-4612-0919-5_37 by Jan deLeeuw edited by Samuel Kotz, NormanL Johnson

@incollection{deleeuw-1992, abstract = {The problem of estimating the dimensionality of a model occurs in various forms in applied statistics: estimating the number of factors in factor analysis, estimating the degree of a polynomial describing the data, selecting the variables to be introduced in a multiple regression equation, estimating the order of an {AR} or {MA} time series model, and so on.}, address = {New York}, author = {deLeeuw, Jan}, booktitle = {Breakthroughs in Statistics}, citeulike-article-id = {13434979}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-1-4612-0919-5\_37}, citeulike-linkout-1 = {http://link.springer.com/chapter/10.1007/978-1-4612-0919-5\_37}, doi = {10.1007/978-1-4612-0919-5\_37}, editor = {Kotz, Samuel and Johnson, Norman L.}, keywords = {math, model-selection, multi-modality, statistics}, pages = {599--609}, posted-at = {2014-11-20 14:25:42}, priority = {2}, publisher = {Springer-Verlag}, series = {Springer Series in Statistics}, title = {Introduction to {A}kaike (1973) Information Theory and an Extension of the Maximum Likelihood Principle}, url = {http://dx.doi.org/10.1007/978-1-4612-0919-5\_37}, year = {1992} }

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Akaike's information criterion is strongly linked to information theory and the maximum likelihood principle.⇒