Efficient ANOVA for directional data

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• 作者：Christophe Ley ; Yvik Swan ; Thomas Verdebout
• 关键词：Directional statistics ; Local asymptotic normality ; Pseudo ; FvML tests ; Rank ; based inference ; ANOVA
• 刊名：Annals of the Institute of Statistical Mathematics
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：69
• 期：1
• 页码：39-62
• 全文大小：
• 刊物类别：Mathematics and Statistics
• 刊物主题：Statistics, general; Statistics for Business/Economics/Mathematical Finance/Insurance;
• 出版者：Springer Japan
• ISSN：1572-9052
• 卷排序：69

文摘

In this paper, we tackle the ANOVA problem for directional data. We apply the invariance principle to construct locally and asymptotically most stringent rank-based tests. Our semi-parametric tests improve on the optimal parametric tests by being valid under the whole class of rotationally symmetric distributions. Moreover, they keep the optimality property of the latter under a given m-tuple of rotationally symmetric distributions. Asymptotic relative efficiencies are calculated and the finite-sample behavior of the proposed tests is investigated by means of a Monte Carlo simulation. We conclude by applying our findings to a real-data example involving geological data.