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This article is cited in 3 scientific papers (total in 3 papers)
Short Communications
The structure of the UMVUEs from categorical data
A. Kagana, M. Konikov a University of Maryland
Abstract:
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:
estimation, linear space, partition, subalgebra, sufficiency.
Received: 16.03.2005
Citation:
A. Kagan, M. Konikov, “The structure of the UMVUEs from categorical data”, Teor. Veroyatnost. i Primenen., 50:3 (2005), 597–604; Theory Probab. Appl., 50:3 (2006), 466–473
Linking options:
https://www.mathnet.ru/eng/tvp100https://doi.org/10.4213/tvp100 https://www.mathnet.ru/eng/tvp/v50/i3/p597
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Abstract page: | 289 | Full-text PDF : | 163 | References: | 33 |
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