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
收藏
页码：91 / 97
页数：7
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