Multiparameter estimation for some multivariate discrete distributions with possibly dependent components
Multiparameter estimation for some multivariate discrete distributions with possibly dependent components
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一些可能具有相关分量的多元离散分布的多参数估计
DOI：
10.1007/bf02482499
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发表时间：
1986
影响因子：
1
通讯作者：
Kam
中科院分区：
文献类型：
--
作者：
Kam
在具有无限支持度的多元离散分布的多参数估计中，当多元概率分布函数不是一维边际概率分布函数的乘积时的不容许性问题以前没有被探讨过。本文探讨了在这些情况下的不可受理的问题。特别注意的是估计负多项分布的平均值。在估计均值向量时，某些Clevenson-Zidek型估计量在一大类一般尺度平方损失函数下一致优于通常的估计量。一些结果被推广到其他多元离散分布和几个独立的负多项式分布的情况下被认为是。
In multiparameter estimation for multivariate discrete distributions with infinite support, inadmissibility problems in situations where the multivariate probability distribution function isnota product of the one-dimensional marginal probability distribution functions have previously been unexplored. This paper examines the inadmissibility problem in some of these situations. Special attention is given to estimating the mean of a negative multinomial distribution. In estimating the mean vector, certain Clevenson-Zidek type estimators are shown to be uniformly better than the usual estimator under a large class of generally scaled squared loss functions. Some of the results are generalized to other multivariate discrete distributions and to situations where several independent negative multinomial distributions are considered.