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Maximum likelihood principle and $I$-divergence: continuous time observations
Kybernetika, Tome 34 (1998) no. 3, pp. 289-308 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 continuous 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 continuous time.
Classification : 62B10, 62F10, 62F12, 62M10
Keywords: maximum likelihood estimation; information divergence; Gaussian process; autoregressive processes 
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     author = {Mich\'alek, Ji\v{r}{\'\i}},
     title = {Maximum likelihood principle and $I$-divergence: continuous time observations},
     journal = {Kybernetika},
     pages = {289--308},
     year = {1998},
     volume = {34},
     number = {3},
     mrnumber = {1640970},
     zbl = {1274.62067},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_1998_34_3_a2/}
}
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Michálek, Jiří. Maximum likelihood principle and $I$-divergence: continuous time observations. Kybernetika, Tome 34 (1998) no. 3, pp. 289-308. http://geodesic.mathdoc.fr/item/KYB_1998_34_3_a2/

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