相关与非等价伯努利随机变量和的极限定理

Q3 Business, Management and Accounting

American Journal of Mathematical and Management Sciences Pub Date : 2020-04-02 DOI:10.1080/01966324.2019.1673266

Deepak Singh, Somesh Kumar

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引用次数: 2

摘要

摘要本文定义了一类新的相关伯努利随机变量。在这里，给定试验的成功概率是成功次数和前几次试验成功概率的函数。推导了该模型的力矩结构。在成功概率为单调的条件下，建立了强大数定律、中心极限定理和迭代对数定律。通过仿真验证了大数定律和中心极限定理。

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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Limit Theorems for Sums of Dependent and Non-Identical Bernoulli Random Variables

SYNOPTIC ABSTRACT In this paper, a new class of dependent Bernoulli random variables is defined. Here the probability of success at a given trial is a function of the number of successes and probabilities of successes in the previous trials. The moment structure for this model is derived. Further, the strong law of large numbers, the central limit theorem and the law of iterated logarithm are established under a condition that the success probabilities be monotone. Simulations are carried out to demonstrate the law of large numbers and the central limit theorem.

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来源期刊

American Journal of Mathematical and Management Sciences Business, Management and Accounting-Business, Management and Accounting (all)

CiteScore

2.70

自引率

0.00%

发文量