实际检测财务欺诈的条件概率--本福德定律的一个数学扩展
Conditional probability of actually detecting a financial fraud - a neutrosophic extension to Benford's law
摘要：
这项研究实际上借鉴和建立在一个较早的文件（Kumar和Bhattacharya，2002年）。在这里，我们基本上为确定金融欺诈实际发生的条件概率的问题增加了一个数学维度，假设在拒绝原假设H 0（观察到的第一位数频率近似于本福德分布）和接受备择假设H1（观察到的第一位数频率不近似于本福德分布）时没有发生第一类错误。我们还提出了一个概念模型，以实现这样一个智能欺诈检测系统。
英文摘要：
This study actually draws from and builds on an earlier paper (Kumar and Bhattacharya, 2002). Here we have basically added a neutrosophic dimension to the problem of determining the conditional probability that a financial fraud has been actually committed, given that no Type I error occurred while rejecting the null hypothesis H0: The observed first-digit frequencies approximate a Benford distribution; and accepting the alternative hypothesis H1: The observed first-digit frequencies do not approximate a Benford distribution. We have also suggested a conceptual model to implement such a neutrosophic fraud detection system.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
