关于均值和方差相等的正态分布的序贯估计

IF 1.6 Q1 STATISTICS & PROBABILITY
S. Nadarajah, I. Okorie
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引用次数: 0

摘要

Mukhopadhyay和Cicconetti \cite{mc2004}导出了$N(θ,θ)$中$θ$的最大似然估计(MLE)和一致最小方差无偏估计(UMVUE),并讨论了它们在$θ$纯序列和两阶段有界风险估计中的应用。在本文中,导出了$\theta$的UMVUE的一个简单得多的表达式。使用该表达式,对基于MLE和UMVUE的序列估计器的性能进行了全面的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On sequential estimation of a normal distribution having equal mean and variance
Mukhopadhyay and Cicconetti \cite{mc2004} derived the Maximum Likelihood Estimator (MLE) and the Uniformly Minimum Variance Unbiased Estimator (UMVUE) of $\theta$ in $N (\theta, \theta)$ and discussed their application to purely sequential and two-stage bounded risk estimation of $\theta$.  In this paper, a much simpler expression is derived for the UMVUE of $\theta$.  Using this expression, a comprehensive investigation is provided for comparing the performances of the sequential estimators based on the MLE and the UMVUE.
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来源期刊
Statistica
Statistica STATISTICS & PROBABILITY-
CiteScore
1.70
自引率
0.00%
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0
审稿时长
10 weeks
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