简单随机抽样和移动极值排序集抽样下形状参数的极大似然估计

IF 0.9 4区数学 Q3 STATISTICS & PROBABILITY

Statistics & Probability Letters Pub Date : 2025-06-04 DOI:10.1016/j.spl.2025.110465

Rui Yang, Wangxue Chen

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引用次数: 0

摘要

本文研究了形状族中形状参数的极大似然估计，重点研究了简单随机抽样（SRS）和移动极值排序集抽样（MERSS）。研究了几种常见形状分布的最大似然值的存在性和唯一性。为了更深入地了解MERSS相对于（w.r.t.）的性能。对于常见的形状分布，本文计算了使用MERSS和使用SRS的MLE的渐近效率。常见形状分布的结果表明，与SRS相比，MERSS提供了一种更有效的形状参数估计方法。此外，我们还研究了不完美排名的影响。

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Maximum likelihood estimator of the shape parameter under simple random sampling and moving extremes ranked set sampling

This paper examines the maximum likelihood estimator (MLE) for the shape parameter from the shape family, focusing on both simple random sampling (SRS) and moving extremes ranked set sampling (MERSS). The study establishes the existence and uniqueness of the MLE for several common shape distributions. In order to give more insight into the performance of MERSS with respect to (w.r.t.) SRS, the asymptotic efficiency of the MLE using MERSS w.r.t. that using SRS is computed for the common shape distributions. The findings from the common shape distributions indicate that MERSS provides a more efficient approach for estimating the shape parameter compared to SRS. Additionally, we examine the implications of imperfect ranking.

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来源期刊

Statistics & Probability Letters 数学-统计学与概率论

CiteScore

1.60

自引率

0.00%

发文量

173

审稿时长

6 months

期刊介绍： Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature. Statistics & Probability Letters is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission. The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of Statistics & Probability Letters is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability. The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published.