Bootstrap and permutation tests in ANOVA for directional data

被引：0
|
作者：
Adelaide Figueiredo
机构：
[1] University of Porto,Faculty of Economics
[2] LIAAD-INESC TEC,undefined
来源：
Computational Statistics | 2017年 / 32卷
关键词：
Hypersphere; Monte Carlo methods; Simulation; Watson distribution; Resampling methods;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The problem of testing the null hypothesis of a common direction across several populations defined on the hypersphere arises frequently when we deal with directional data. We may consider the Analysis of Variance (ANOVA) for testing such hypotheses. However, for the Watson distribution, a commonly used distribution for modeling axial data, the ANOVA test is only valid for large concentrations. So we suggest to use alternative tests, such as bootstrap and permutation tests in ANOVA. Then, we investigate the performance of these tests for data from Watson populations defined on the hypersphere.
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页码：1213 / 1240
页数：27
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