On the Nuisance Parameter Elimination Principle in Hypothesis Testing

被引:0
|
作者
Florez Rivera, Andres Felipe [1 ]
Esteves, Luis Gustavo [1 ]
Fossaluza, Victor [1 ]
de Braganca Pereira, Carlos Alberto [1 ]
机构
[1] Univ Sao Paulo, Inst Math & Stat, BR-05508090 Sao Paulo, Brazil
关键词
p-values; Bayes factor; likelihood function; hypothesis testing; BIRNBAUM ARGUMENT; MARGINAL HOMOGENEITY; SYMMETRY;
D O I
10.3390/e26020117
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The Non-Informative Nuisance Parameter Principle concerns the problem of how inferences about a parameter of interest should be made in the presence of nuisance parameters. The principle is examined in the context of the hypothesis testing problem. We prove that the mixed test obeys the principle for discrete sample spaces. We also show how adherence of the mixed test to the principle can make performance of the test much easier. These findings are illustrated with new solutions to well-known problems of testing hypotheses for count data.
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页数:24
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