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Maximum likelihood principle and $I$-divergence: discrete time observations
Kybernetika, Tome 34 (1998) no. 3, pp. 265-288 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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The paper investigates the relation between maximum likelihood and minimum $I$-divergence estimates of unknown parameters and studies the asymptotic behaviour of the likelihood ratio maximum. Observations are assumed to be done in the discrete time.
The paper investigates the relation between maximum likelihood and minimum $I$-divergence estimates of unknown parameters and studies the asymptotic behaviour of the likelihood ratio maximum. Observations are assumed to be done in the discrete time.
Classification : 62B10, 62F12, 62M10
Keywords: maximum likelihood estimate; information divergence; exponential families; discrete time process; autoregressive sequences 
@article{KYB_1998_34_3_a1,
     author = {Mich\'alek, Ji\v{r}{\'\i}},
     title = {Maximum likelihood principle and $I$-divergence: discrete time observations},
     journal = {Kybernetika},
     pages = {265--288},
     year = {1998},
     volume = {34},
     number = {3},
     mrnumber = {1640966},
     zbl = {1274.62066},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_1998_34_3_a1/}
}
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Michálek, Jiří. Maximum likelihood principle and $I$-divergence: discrete time observations. Kybernetika, Tome 34 (1998) no. 3, pp. 265-288. http://geodesic.mathdoc.fr/item/KYB_1998_34_3_a1/

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