Jeffreys先验得到渐近极大极小冗余

Proceedings of 1994 Workshop on Information Theory and Statistics Pub Date : 1994-10-27 DOI:10.1109/WITS.1994.513856

B. S. Clarke, A. Barron

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引用次数: 1

摘要

我们确定了在参数设置下通用数据压缩的渐近极大极小冗余，并证明了它对应于杰弗里斯先验的使用。从统计学上讲，这个编码问题的公式可以在先验选择上下文和估计上下文中解释。

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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Jeffreys' prior yields the asymptotic minimax redundancy

We determine the asymptotic minimax redundancy of universal data compression in a parametric setting and show that it corresponds to the use of Jeffreys prior. Statistically, this formulation of the coding problem can be interpreted in a prior selection context and in an estimation context.

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Proceedings of 1994 Workshop on Information Theory and Statistics

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