Information Theory and an Extension of the Maximum Likelihood Principle
Information Theory and an Extension of the Maximum Likelihood Principle
Key takeaways
Bibliography: Akaike, H., 1998. Information Theory and an Extension of the Maximum Likelihood Principle, in: Parzen, E., Tanabe, K., Kitagawa, G. (Eds.), Selected Papers of Hirotugu Akaike, Springer Series in Statistics. Springer New York, New York, NY, pp. 199–213. https://doi.org/10.1007/978-1-4612-1694-0_15
Authors:: Emanuel Parzen, Kunio Tanabe, Genshiro Kitagawa, Hirotogu Akaike
Collections:: Methods
First-page:
Abstract In this paper it is shown that the classical maximum likelihood principle cInanthibsepacponersiidt eisresdhotwonbtehaat tmheecthlaosdsicoafl masayxmimptuomticlikreelailhiozaotdiopnrinocfipalne coapntimbeumcoensstiidmearteedwtiothbreesapemctettohoadveorfy agseynmerpatloitnicforremaalitzioantiotnheoorfetainc corpitteimriounm. Teshtiismoabtesewrvitahtiroenspsehcotwtos aanveexrytegnesnioenraol finthfoerpmrainticoipnlethteoorpertoiccvriditeerainosnw. Terhsistoombsaenrvyaptiroanctischaolwpsroabnleemxtsenosfisotnatiosftitchael pmroindceilplfeitttiongp. rovide answers to many practical problems of statistical model fitting.
content: "@akaikeInformationTheoryExtension1998" -file:@akaikeInformationTheoryExtension1998