On logarithmic derivatives of probability densities

A. V. Rezbaev
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Abstract

We construct two examples connected with the integrability of logarithmic derivatives of probability densities on the real line, in particular, with the Fisher information number. These examples show that the Fisher information of a probability density cannot be estimated in terms of L^1 -norms of its first and second derivatives and the maximum of the absolute value of the second derivative. In addition, the norm of the logarithmic derivative of the density in L^3 cannot be estimated in terms of the norms in L^1 of the derivatives of the density of any order.
关于概率密度的对数导数
我们构造了两个与概率密度的对数导数在实线上的可积性有关的例子,特别是用Fisher信息数。这些例子表明,概率密度的Fisher信息不能用一阶和二阶导数的L^1范数和二阶导数绝对值的最大值来估计。此外,密度在L^3中的对数导数的范数不能用密度在L^1中的任何阶的导数的范数来估计。
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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