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A Generalized φ-Divergence for Asymptotically Multivariate Normal Models

✍ Scribed by Stefan Wegenkittl

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
156 KB
Volume
83
Category
Article
ISSN
0047-259X

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✦ Synopsis

gives a goodness-of-fit statistic for multinomial distributed data. We define a generalized f-divergence that unifies the j-divergence approach with that of C. R. Rao and S. K. Mitra (''Generalized Inverse of Matrices and Its Applications,' ' Wiley, New York, 1971) and derive weak convergence to a q 2 distribution under the assumption of asymptotically multivariate normal distributed data vectors. As an example we discuss the application to the frequency count in Markov chains and thereby give a goodness-of-fit test for observations from dependent processes with finite memory.

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