摘要:

When testing whether two samples came from a common distribution against the alternative that they differ in scale, the asymptotically most powerful rank test depends on the density function underlying the data. In some applications it is only known that the data are from a gamma distribution with increasing hazard rate (i.e., the value of the shape parameter,k, is known to be ≥ 1). If the optimum test (Savage 1956) for data from an exponential law (k= 1) is used when the true value ofkis much larger, a loss of power or asymptotic relative efliciency results. Indeed, the ARE of the exponential scores test relative to the optimum rank test for largek(∞) is about 81.4%. This article presents the maximin efficiency robust test for the gamma (k≥ 1) family that has an asymptotic efficiency of at least 95% relative to the optimum test for each member of the family. The test can be calculated using standard statistical packages and is illustrated on real data.

ISSN:0040-1706    

DOI:10.1080/00401706.1986.10488101

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

ISSN:0040-1706    

DOI:10.1080/00401706.1986.10488104

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

ISSN:0040-1706    

DOI:10.1080/00401706.1986.10488105

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

ISSN:0040-1706    

DOI:10.1080/00401706.1986.10488106

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

ISSN:0040-1706    

DOI:10.1080/00401706.1986.10488107

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

ISSN:0040-1706    

DOI:10.1080/00401706.1986.10488108

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor

ISSN:0040-1706    

DOI:10.1080/00401706.1986.10488109

出版商:Taylor & Francis Group    

年代:1986

数据来源: Taylor