| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1111/1467-842X.00049 |
| Theory & Methods: Distance Testing for Selecting the Best Population. | |
| Futschik A; Pflug G | |
| 发表日期 | 1998 |
| 出处 | Australian & New Zealand Journal of Statistics 40 (4): 443-464 |
| 出版年 | 1998 |
| 语种 | 英语 |
| 摘要 | Consider testing the null hypothesis that a given population has location parameter greater than or equal to the largest location parameter of k competing populations. This paper generalizes tests proposed by Gupta and Bartholomew by considering tests based on p-distances from the parameter estimate to the null parameter space. It is shown that all tests are equivalent when k[RIGHTWARDS ARROW]∞ for a class of distributions that includes the normal and the uniform. The paper proposes the use of adaptive quantiles. Under suitable assumptions the resulting tests are asymptotically equivalent to the uniformly most powerful test for the case that the location parameters of all but one of the populations are known. The increase in power obtained by using adaptive tests is confirmed by a simulation study. |
| 主题 | Risk, Modeling, Policy (RMP) |
| 关键词 | subset selection simple tree order distance tests efficient adaptive testing order restricted inference extreme order statistics |
| URL | http://pure.iiasa.ac.at/id/eprint/5405/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/127761 |
| 推荐引用方式 GB/T 7714 | Futschik A,Pflug G. Theory & Methods: Distance Testing for Selecting the Best Population.. 1998. |
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