Using Model Selection Criteria to Choose the Number of Principal Components

被引：4

作者：

Sclove, Stanley L. ^{[1
]}

机构：

[1] Univ Illinois, Chicago, IL 60607 USA

来源：

JOURNAL OF STATISTICAL THEORY AND APPLICATIONS | 2021年 / 20卷 / 03期

关键词：

Information criteria; AIC; BIC; Principal components; REGRESSION;

D O I：

10.1007/s44199-021-00002-4

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The use of information criteria, especially AIC (Akaike's information criterion) and BIC (Bayesian information criterion), for choosing an adequate number of principal components is illustrated.

引用

页码：450 / 461

页数：12

共 14 条

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