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连续最大熵推理中的共轭变量。

Conjugate variables in continuous maximum-entropy inference.

作者信息

Davis Sergio, Gutiérrez Gonzalo

机构信息

Grupo de Nanomateriales, Departamento de Física, Facultad de Ciencias, Universidad de Chile, Casilla 653, Santiago, Chile.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Nov;86(5 Pt 1):051136. doi: 10.1103/PhysRevE.86.051136. Epub 2012 Nov 28.

Abstract

For a continuous maximum-entropy distribution (obtained from an arbitrary number of simultaneous constraints), we derive a general relation connecting the Lagrange multipliers and the expectation values of certain particularly constructed functions of the states of the system. From this relation, an estimator for a given Lagrange multiplier can be constructed from derivatives of the corresponding constraining function. These estimators sometimes lead to the determination of the Lagrange multipliers by way of solving a linear system, and, in general, they provide another tool to widen the applicability of Jaynes's formalism. This general relation, especially well suited for computer simulation techniques, also provides some insight into the interpretation of the hypervirial relations known in statistical mechanics and the recently derived microcanonical dynamical temperature. We illustrate the usefulness of these new relations with several applications in statistics.

摘要

对于连续的最大熵分布(由任意数量的同时约束条件获得),我们推导出一个通用关系,该关系将拉格朗日乘数与系统状态的某些特别构造函数的期望值联系起来。基于此关系,可以从相应约束函数的导数构造给定拉格朗日乘数的估计量。这些估计量有时会通过求解线性系统来确定拉格朗日乘数,并且一般来说,它们提供了另一种工具来拓宽杰恩斯形式主义的适用性。这个通用关系特别适合计算机模拟技术,它还为统计力学中已知的超维里关系和最近推导的微正则动力学温度的解释提供了一些见解。我们通过统计学中的几个应用来说明这些新关系的有用性。

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