An Information Theoretic Approach To Probability Mass Function Truncation
2019 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT)(2019)
摘要
Given a discrete random variable X that takes values in a finite set X according to a probability mass function (pmf) P, a truncated pmf Q of P is a conditional pmf that results from restricting the domain of X to some subset of X. Truncated pmf arise in several problems of statistics and probability. In this paper, we propose and analyze a few criteria to truncate pmf's so that the truncated one is as much close as possible to the original pmf, under different information theoretic measures of distance.
更多查看译文
关键词
probability mass function truncation,information theoretic approach,discrete random variable
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络