Fuzzy data treated as functional data: A one-way ANOVA test approach

被引:112
|
作者
Gonzalez-Rodriguez, Gil [1 ]
Colubi, Ana [2 ]
Angeles Gil, Maria [2 ]
机构
[1] European Ctr Soft Comp, Mieres 33600, Asturias, Spain
[2] Univ Oviedo, Dept Estadist IO & DM, E-33071 Oviedo, Spain
关键词
Functional data; Fuzzy data; k-samples test; ANOVA statistic; Hilbert space; Convex cone; Bootstrap; Local alternatives; RANDOM-VARIABLES; BOOTSTRAP TECHNIQUES; REPRESENTATION;
D O I
10.1016/j.csda.2010.06.013
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The use of the fuzzy scale of measurement to describe an important number of observations from real-life attributes or variables is first explored. In contrast to other well-known scales (like nominal or ordinal), a wide class of statistical measures and techniques can be properly applied to analyze fuzzy data. This fact is connected with the possibility of identifying the scale with a special subset of a functional Hilbert space. The identification can be used to develop methods for the statistical analysis of fuzzy data by considering techniques in functional data analysis and vice versa. In this respect, an approach to the FANOVA test is presented and analyzed, and it is later particularized to deal with fuzzy data. The proposed approaches are illustrated by means of a real-life case study. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:943 / 955
页数:13
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