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arXiv 2103.11038math.PRcs.ITmath.ITmath.STstat.TH
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由概率密度函数诱导的分布的随机比较、微分熵与 varentropy

Stochastic comparisons, differential entropy and varentropy for distributions induced by probability density functions

Antonio Di Crescenzo, Luca Paolillo, Alfonso Suarez-Llorens

AI总结:

本文提出 pdf 相关分布,研究其分布形式、分位数与可靠性性质,并利用随机序进行比较,进而分析微分熵和 varentropy 等信息测度。

摘要:

受描述与信息测度相关的有用概念之需求所激发,我们引入了“pdf 相关分布”。这些分布通过绝对连续随机变量经其自身概率密度函数的变换来定义。我们研究了它们的主要特征,涉及分布的一般形式、分位数以及可靠性理论中的一些相关概念。这使我们能够获得 pdf 相关分布为均匀分布的一个刻画,该刻画同样适用于指数型和 Laplace 型分布。我们还通过借助适当的随机序来处理 pdf 相关分布的随机比较问题。最后,利用所得结果分析性质并比较一些有用的信息测度,例如微分熵和 varentropy。

英文摘要:

Stimulated by the need of describing useful notions related to information measures, we introduce the `pdf-related distributions'. These are defined in terms of transformation of absolutely continuous random variables through their own probability density functions. We investigate their main characteristics, with reference to the general form of the distribution, the quantiles, and some related notions of reliability theory. This allows us to obtain a characterization of the pdf-related distribution being uniform for distributions of exponential and Laplace type as well. We also face the problem of stochastic comparing the pdf-related distributions by resorting to suitable stochastic orders. Finally, the given results are used to analyse properties and to compare some useful information measures, such as the differential entropy and the varentropy.

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。

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