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Multivariate testing and model-checking for generalized order statistics with applications

机译:应用程序对通用订单统计进行多变量测试和模型检查

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摘要

The exponential family structure of the joint distribution of generalized order statistics is utilized to establish multivariate tests on the model parameters. For simple and composite null hypotheses, the likelihood ratio test (LR test), Wald's test, and Rao's score test are derived and turn out to have simple representations. The asymptotic distribution of the corresponding test statistics under the null hypothesis is stated, and, in case of a simple null hypothesis, asymptotic optimality of the LR test is addressed. Applications of the tests are presented; in particular, we discuss their use in reliability, and to decide whether a Poisson process is homogeneous. Finally, a power study is performed to measure and compare the quality of the tests for both, simple and composite null hypotheses.
机译:利用广义顺序统计量联合分布的指数族结构,对模型参数建立多元检验。对于简单和合成的零假设,似然比检验(LR检验),Wald检验和Rao得分检验得到了推导,结果证明它们具有简单的表示形式。陈述了在零假设下相应检验统计量的渐近分布,并且在简单零假设的情况下,解决了LR检验的渐近最优性。介绍了测试的应用;特别是,我们讨论了它们在可靠性方面的用途,并确定泊松过程是否同质。最后,进行了功效研究,以测量和比较简单和复合无效假设的测试质量。

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