A unified approach to goodness-of-fit testing for spherical and hyperspherical data

被引：1

作者：

Ebner, Bruno ^{[1
]}

Henze, Norbert ^{[1
]}

Meintanis, Simos ^{[2
,3
]}

机构：

[1] Karlsruhe Inst Technol KIT, Inst Stochast, Englerstr 2, D-76133 Karlsruhe, Germany

[2] Natl & Kapodistrian Univ Athens, Dept Econ, Athens, Greece

[3] North West Univ, Pure & Appl Analyt, Potchefstroom, South Africa

来源：

STATISTICAL PAPERS | 2024年 / 65卷 / 06期

关键词：

Goodness-of-fit test; Characteristic function; Resampling methods; Spherical distribution; 2-SAMPLE PROBLEM; STATISTICS; UNIFORMITY;

D O I：

10.1007/s00362-024-01529-1

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We propose a general and relatively simple method to construct goodness-of-fit tests on the sphere and the hypersphere. The method is based on the characterization of probability distributions via their characteristic function, and it leads to test criteria that are convenient regarding applications and consistent against arbitrary deviations from the model under test. We emphasize goodness-of-fit tests for spherical distributions due to their importance in applications and the relative scarcity of available methods.

引用

页码：3447 / 3475

页数：29

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