Comparing a new algorithm with the classic methods for estimating the number of factors

被引：74

作者：

Henry, RC

Park, ES

Spiegelman, CH

机构：

[1] Univ So Calif, Dept Civil & Environm Engn, Environm Engn Program, Los Angeles, CA 90089 USA

[2] Univ Washington, Natl Res Ctr Stat & Environm, Seattle, WA 98195 USA

[3] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 1999年 / 48卷 / 01期

基金：

美国国家科学基金会;

关键词：

number of factors; correlation matrix; eigenvalues; eigenvectors; Bartlett's test; scree plots; Malinowski's indicator function; cross-validation; NUMFACT;

D O I：

10.1016/S0169-7439(99)00015-5

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents and compares a new algorithm for finding the number of factors in a data analytic model. After we describe the new method, called NUMFACT, we compare it with standard methods for finding the number of factors to use in a model. The standard methods that we compare NUMFACT with are Malinowski's indicator function, Weld's cross-validation approach, Bartlett's test, scree plots, the rule-of-one, and using the number of factors (eigenvectors) needed to explain 90% of the trace of a correlation matrix. Using a diverse set of real applications, NUMFACT is shown to be the clear method of choice. (C) 1999 Elsevier Science B.V. All rights reserved.

引用

页码：91 / 97

页数：7

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