Homogeneity analysis withk sets of variables: An alternating least squares method with optimal scaling features
Homogeneity analysis withk sets of variables: An alternating least squares method with optimal scaling features
复制标题
使用 k 组变量进行同质性分析：具有最佳缩放特征的交替最小二乘法
DOI：
10.1007/bf02294131
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发表时间：
1988
期刊：
影响因子：
3
通讯作者：
R. Verdegaal
中科院分区：
文献类型：
--
作者：
E. V. D. Burg;J. Leeuw;R. Verdegaal
齐性分析或多重对应分析通常应用于k个独立变量。在本文中，我们通过使用集合中的和来将它应用于变量集合。由此产生的技术被称为OVERALS。它使用最佳缩放的概念，变换可以是多个也可以是单一的。单一转换由三种类型组成：名义、顺序和数值。相应的OVERALS计算机程序通过使用交替最小二乘算法来最小化最小二乘损失函数。许多现有的线性和非线性多元分析技术都是OVERALS的特例。给出了一个流行病学调查数据的应用。
Homogeneity analysis, or multiple correspondence analysis, is usually applied to k separate variables. In this paper we apply it to sets of variables by using sums within sets. The resulting technique is called OVERALS. It uses the notion of optimal scaling, with transformations that can be multiple or single. The single transformations consist of three types: nominal, ordinal, and numerical. The corresponding OVERALS computer program minimizes a least squares loss function by using an alternating least squares algorithm. Many existing linear and nonlinear multivariate analysis techniques are shown to be special cases of OVERALS. An application to data from an epidemiological survey is presented.