Exponential-Poisson Parameters Estimation in Moving Extremes Ranked Set Sampling Design

IF 0.9 4区数学 Q3 MATHEMATICS, APPLIED

Acta Mathematicae Applicatae Sinica, English Series Pub Date : 2025-10-06 DOI:10.1007/s10255-023-1076-1

Meng Chen, Wang-xue Chen, Rui Yang, Ya-wen Zhou

引用次数: 0

Abstract

In this article, the maximum likelihood estimators (MLEs) of the scale and shape parameters β and λ from the Exponential-Poisson distribution will be considered in moving extremes ranked set sampling (MERSS). These MLEs will be compared in terms of asymptotic efficiencies. The numerical results show that the MLEs obtained via MERSS can serve as effective alternatives to those derived from simple random sampling.

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移动极值排序集抽样设计中的指数泊松参数估计

在本文中，从指数泊松分布的尺度和形状参数β和λ的最大似然估计（MLEs）将考虑在移动极值排序集抽样（MERSS）。我们将从渐近效率的角度来比较这些mle。数值计算结果表明，该方法可以有效地替代简单随机抽样方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Acta Mathematicae Applicatae Sinica, English Series 数学-应用数学

CiteScore

1.30

自引率

0.00%

发文量

审稿时长

3.0 months

期刊介绍： Acta Mathematicae Applicatae Sinica (English Series) is a quarterly journal established by the Chinese Mathematical Society. The journal publishes high quality research papers from all branches of applied mathematics, and particularly welcomes those from partial differential equations, computational mathematics, applied probability, mathematical finance, statistics, dynamical systems, optimization and management science.