INFORMATION GAIN AND A GENERAL MEASURE OF CORRELATION
INFORMATION GAIN AND A GENERAL MEASURE OF CORRELATION
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DOI：
10.1093/biomet/70.1.163
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发表时间：
1983-01-01
期刊：
影响因子：
2.7
通讯作者：
KENT, JT
中科院分区：
文献类型：
--
作者：
KENT, JT
给定两个随机变量Xandy之间的相关性的参数模型，信息增益的概念可以用来定义相关性的度量。这种相关性的定义既推广了二元正态模型通常的积矩相关系数，又推广了标准线性回归模型的多重相关系数。研究了这种基于信息的相关性在描述性统计分析中的应用，并给出了几个例子。
Given a parametric model of dependence between two random quantities,XandY, the notion of information gain can be used to define a measure of correlation. This definition of correlation generalizes both the usual product-moment correlation coeffi cient for the bivariate normal model and the multiple correlation coefficient in the standard linear regression model. The use of this information-based correlation in a descriptive statistical analysis is examined and several examples are given.