Assessing the Stability of Supplementary Elements on Principal Axes Maps Through Bootstrap Resampling. Contribution to Interpretation in Textual Analysis

被引：0

作者：

Alvarez-Esteban, Ramon

Valencia, Olga ^{[1
]}

Becue-Bertaut, Monica ^{[2
]}

机构：

[1] Univ Burgos, Dept Appl Econom, Burgos 09001, Spain

[2] Univ Politecn Cataluna, Dept Stat & Operat Res, Barcelona 08034, Spain

来源：

ADVANCES IN DATA ANALYSIS: THEORY AND APPLICATIONS TO RELIABILITY AND INFERENCE, DATA MINING, BIOINFORMATICS, LIFETIME DATA, AND NEURAL NETWORKS | 2010年

关键词：

Correspondence analysis; bootstrap; textual analysis; free-text comments;

D O I：

10.1007/978-0-8176-4799-5_1

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：

Bootstrap resampling is commonly used to assess the stability of the configurations issued from principal axes methods. In the case of textual analysis, the interpretation is usually supported by the characteristics of the individuals, used as supplementary variables. To assess the stability of these variables gives information about the global structure stability. An example issued from a wine guide illustrates the interest of computing confidence regions for supplementary, categorical or quantitative variables in correspondence analysis applied to lexical tables.

引用

页码：3 / +

页数：3