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AI 根据所提供的论文材料归类:摘要研究二元位置与方向统计检验,没有足够文本依据归入所列经济计量细分。

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代码、数据与补充材料

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关注这篇论文的作者
Hannu Oja
Jukka Nyblom

二元符号检验

研究问题
如何检验二元分布的未知对称中心,使检验在非奇异线性变换下保持不变,并评价其局部功效与渐近效率?
方法与思路
作者构造局部最强不变符号检验族,利用观测方向角推导零假设和邻近备择下的极限分布及相对效率。
材料陈述的贡献
摘要称,既有二元符号检验可纳入该检验族,并给出效率及下界结果,讨论配对比较与圆周分布检验应用。
阅读关注点
核对对称性及椭圆备择的具体要求、局部最优性的限定范围,以及效率下界与显著性水平和功效的关系。
阅读边界
仅据版本未注明的 OpenAlex 索引摘要;最优性与效率结论有特定备择范围,配对比较应用仍须核对所述中心对称性前提。

原文摘要

In this article the bivariate location problem is treated. New appealing bivariate analogs of the univariate sign tests are proposed for testing the null hypothesis concerning the unknown symmetry center. These tests remain unaltered under any nonsingular linear transformation. From these promising findings a whole family of locally most powerful invariant sign tests is introduced. The tests proposed earlier (Blumen 1958; Hodges 1955) are specific members of this family. For example, Blumen's test appears to be optimal against bivariate normal (or any other elliptic) alternatives. The limiting distributions are derived both under the null hypothesis and under the contiguous alternatives. These limiting distributions are then used to derive asymptotic relative efficiencies. It is found that Blumen's test has the efficiency .785 relative to Hotelling's test against bivariate normal alternatives. For other locally most powerful sign tests the corresponding efficiency depends on the significance level and the power, but not too strongly. In fact, the value .785 also serves as an approximation for other sign tests. The lower bound for the efficiency of Blumen's test relative to Hotelling's test is established against elliptic alternatives. The restriction to unimodal elliptic alternatives increases the lower bound to ½. Finally, some results on Hodges's test are included. Bivariate sign tests can be applied, for example, in paired comparison situations with a bivariate response variable. The hypothesis of no difference between two treatments then implies that the paired response differences are symmetric about the origin, which can be tested by using bivariate sign tests. No extra assumptions concerning the unknown bivariate distributions are needed. In addition, other examples of applications are included. The proposed tests use the direction angles of the observations. Therefore, they can be used also in testing the uniformity (and a kind of symmetry) of a circular distribution. In Tables 1, 2, and 3 critical values for three different sign tests are given.

笔记与分组
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