The structure of the UMVUEs from categorical data
Teoriâ veroâtnostej i ee primeneniâ, Tome 50 (2005) no. 3, pp. 597-604 Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice de l'article

Let an observation $X$ take finitely many values with probabilities $p_1(\theta),\ldots,p_N(\theta)$ depending on an abstract parameter $\theta\in\Theta$. It is proved that a statistic is a uniformly minimum variance unbiased estimator (UMVUE) if and only if it is measurable with respect to a subalgebra of the finite algebra generated by $X$. In general, this subalgebra is smaller than the minimal sufficient subalgebra for $\theta$ and is explicitly described. It is related to a special partition of a finite set of elements of an abstract linear space.
Keywords: linear space, sufficiency.
Mots-clés : estimation, partition, subalgebra
@article{TVP_2005_50_3_a14,
     author = {A. Kagan and M. Konikov},
     title = {The structure of the {UMVUEs} from categorical data},
     journal = {Teori\^a vero\^atnostej i ee primeneni\^a},
     pages = {597--604},
     year = {2005},
     volume = {50},
     number = {3},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/TVP_2005_50_3_a14/}
}
TY  - JOUR
AU  - A. Kagan
AU  - M. Konikov
TI  - The structure of the UMVUEs from categorical data
JO  - Teoriâ veroâtnostej i ee primeneniâ
PY  - 2005
SP  - 597
EP  - 604
VL  - 50
IS  - 3
UR  - http://geodesic.mathdoc.fr/item/TVP_2005_50_3_a14/
LA  - en
ID  - TVP_2005_50_3_a14
ER  - 
%0 Journal Article
%A A. Kagan
%A M. Konikov
%T The structure of the UMVUEs from categorical data
%J Teoriâ veroâtnostej i ee primeneniâ
%D 2005
%P 597-604
%V 50
%N 3
%U http://geodesic.mathdoc.fr/item/TVP_2005_50_3_a14/
%G en
%F TVP_2005_50_3_a14
A. Kagan; M. Konikov. The structure of the UMVUEs from categorical data. Teoriâ veroâtnostej i ee primeneniâ, Tome 50 (2005) no. 3, pp. 597-604. http://geodesic.mathdoc.fr/item/TVP_2005_50_3_a14/

[1] Bahadur R. R., “On unbiased estimates of uniformly minimum variance”, Sankhyā, 18 (1957), 211–224 | MR | Zbl

[2] Bondesson L., “On uniformly minimum variance unbiased estimation when no complete sufficient statistics exist”, Metrika, 30:1 (1983), 49–54 | DOI | MR | Zbl

[3] Kagan A. M., Linnik Yu. V., “Nesmeschennoe otsenivanie dlya nepolnykh eksponentsialnykh semeistv”, Transactions of the Fourth Prague Conference on Information Theory, Statistical Decision Functions, Random Processes (Prague, 1965), Academia, Prague, 1967, 389–398 | MR

[4] Kagan A. M., Palamodov V. P., “Nepolnye eksponentsialnye semeistva i nesmeschennye otsenki s naimenshei dispersiei”, Teoriya veroyatn. i ee primen., 12:1 (1967), 39–50 | MR

[5] Kagan A. M., Linnik Yu. V., Rao S. R., Kharakterizatsionnye zadachi matematicheskoi statistiki, Nauka, M., 1972, 656 pp. | MR

[6] Leman E., Teoriya tochechnogo otsenivaniya, Nauka, M., 1991, 444 pp. | MR

[7] Linnik Yu. V., Statisticheskie zadachi s meshayuschimi parametrami, Nauka, M., 1966, 252 pp. | MR

[8] Rao C. R., “Some theorems on minimum variance estimation”, Sankhyā, 12 (1952), 27–42 | MR | Zbl