Equality Constraints in Multiple Correspondence Analysis.
Equality Constraints in Multiple Correspondence Analysis.
复制标题
多重对应分析中的等式约束。
DOI：
10.1207/s15327906mbr2704_4
复制
发表时间：
1992
影响因子：
3.8
通讯作者：
J. Leeuw
中科院分区：
文献类型：
--
作者：
S. Buuren;J. Leeuw
对变量类别应用等式约束是多重对应分析的简单但有用的扩展。等式可用于合并有关类别之间关系的先验知识。类别可以属于同一变量、不同变量或两者。最简单的相等形式指定所有变量接收相同的数据转换。例如，如果在多个时间点测量同一变量，则这很有用。本文概述了处理不相等类别数和变量子集的过程。尽管技术成果并不难得出，但并不为人所知。一些应用说明了该方法。
The application of equality constraints on the categories of a variable is a simple but useful extension of multiple correspondence analysis. Equality can be used to incorporate prior knowledge about the relations between categories. Categories may belong to the same variable, to different variables, or both. The simplest form of equality specifies that all variables receive identical data transforms. This is useful, for example, if the same variable is measured on many points of time. This article outlines a procedure to deal with unequal category numbers and with subsets of variables. Though the technical results are not difficult to derive, they are not very well-known. Some applications illustrate the method.