Bootstrap Comparison of Statistics for Testing the Homoscedasticity of Random Fuzzy Sets

被引：0
|
作者：
Belen Ramos-Guajardo, Ana [1 ]
Asuncion Lubiano, Maria [1 ]
Gonzalez-Rodriguez, Gil [1 ]
机构：
[1] Univ Oviedo, Dept Stat Operat Res & Math Didact, Oviedo, Spain
来源：
SYNERGIES OF SOFT COMPUTING AND STATISTICS FOR INTELLIGENT DATA ANALYSIS | 2013年 / 190卷
关键词：
Bartlett test; bootstrap approach; homoscedasticity; Levene test; random fuzzy sets; SAMPLE TESTS; HOMOGENEITY; VARIANCE;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The problem of testing the equality of variances of k random fuzzy sets has been recently developed on the basis of Levene's classical procedure. Asymptotic and bootstrap approaches have been carried out in this framework, and the proposed test was compared with a Bartlett-type test. In this work, a deeper comparison between some bootstrap statistics based on both Levene's and Bartlett's classical procedures for testing the homoscedasticity of several random fuzzy sets is analyzed. The empirical behaviour of those statistics is investigated by means of simulation studies concerning both type I and type II errors.
引用
收藏
页码：125 / 133
页数：9
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