选择社会经济数据中信息量最大的变量的实验

ORiON Pub Date : 2014-01-01 DOI:10.5784/19-0-181
L. Jenkins
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引用次数: 0

摘要

在许多收集多个变量数据的研究中,有一种动机是发现更少的变量是否能提供几乎同样多的信息。变量关于其均值的方差是信息内容的常用统计度量,这里使用的就是方差。我们感兴趣的是,一个变量的可变性是否与一个或多个其他变量的可变性充分相关,以至于第一个变量是冗余的。我们希望找到一个或多个充分反映所有原始变量中的信息内容的“主变量”。本文解释了主变量的方法,并报告了使用该技术的实验,以确定仅几个变量是否足以反映世界银行数据库中130个国家的11个社会经济变量的信息。虽然主变量法在统计意义上是非常成功的,但世界银行的数据每年变化很大,这表明较少的变量不足以获得该数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An experiment on selecting most informative variables in socio-economic data
In many studies where data are collected on several variables, there is a motivation to find if fewer variables would provide almost as much information. Variance of a variable about its mean is the common statistical measure of information content, and that is used here. We are interested whether the variability in one variable is sufficiently correlated with that in one or more of the other variables that the first variable is redundant. We wish to find one or more ‘principal variables’ that sufficiently reflect the information content in all the original variables. The paper explains the method of principal variables and reports experiments using the technique to see if just a few variables are sufficient to reflect the information in 11 socioeconomic variables on 130 countries from a World Bank (WB) database. While the method of principal variables is highly successful in a statistical sense, the WB data varies greatly from year to year, demonstrating that fewer variables wo uld be inadequate for this data.
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