EDA on the asymptotic normality of the standardized sequential stopping times, Part-II: Distribution-free models

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY

Sequential Analysis-Design Methods and Applications Pub Date : 2020-07-02 DOI:10.1080/07474946.2020.1823193

N. Mukhopadhyay, Chen Zhang

引用次数: 3

Abstract

Abstract In sequential analysis, an experimenter gathers information regarding an unknown functional (parameter) by observing random samples in successive steps. We discuss a number of distribution-free scenarios under a variety of loss functions. The number of observations gathered upon termination is a positive integer-valued random variable, customarily denoted by N. Often, a standardized version of N would follow an approximate normal distribution in the asymptotic sense. We provide exploratory data analysis (EDA) with the help of a number of interesting illustrations. We do so via large-scale simulation studies to demonstrate broad applicability of the purely sequential methodologies along with the appropriateness of asymptotic normality of the standardized stopping variables as a practical and useful guideline.

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标准化顺序停车时间渐近正态性的EDA，第二部分:无分布模型

在序列分析中，实验者通过连续观察随机样本来收集关于未知功能(参数)的信息。我们讨论了在各种损失函数下的一些无分布情形。在终止时收集到的观测值的数量是一个正整数随机变量，通常用N表示。通常，N的标准化版本将遵循渐进意义上的近似正态分布。我们在一些有趣的插图的帮助下提供探索性数据分析(EDA)。我们通过大规模的模拟研究来证明纯序列方法的广泛适用性，以及标准化停止变量的渐近正态性作为实用和有用的指导方针的适当性。

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

Sequential Analysis-Design Methods and Applications STATISTICS & PROBABILITY-

CiteScore

1.40

自引率

12.50%

发文量

期刊介绍： The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches. Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.