文章基本信息

标题：Multiway empirical likelihood
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作者：Harold D Chiang ; Yukitoshi Matsushita ; Taisuke Otsu 等
期刊名称：Distributional Analysis Publications
印刷版ISSN：1352-2469
出版年度：2021
卷号：2021
页码：1-30
语种：English
出版社：Suntory Toyota International Centres for Economics and Related Disciplines
摘要：his paper develops a general methodology to conduct statistical inference for observations indexed by multiple sets of entities. We propose a novel multiway empirical likeli- hood statistic that converges to a chi-square distribution under the non-degenerate case, where corresponding Hoeffding type decomposition is dominated by linear terms. Our methodology is related to the notion of jackknife empirical likelihood but the leave-out pseudo values are constructed by leaving out columns or rows. We further develop a modified version of our multiway empirical likelihood statistic, which converges to a chi-square distribution regardless of the degeneracy, and discover its desirable higher-order property compared to the t-ratio by the conventional Eicker-White type variance estimator. The proposed methodology is illus- trated by several important statistical problems, such as bipartite network, two-stage sampling, generalized estimating equations, and three-way observations.
关键词：multiway data;empirical likelihood;bipartite network