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Multivariate testing and model-checking for generalized order statistics with applications
Authors:Stefan Bedbur  Eric Beutner  Udo Kamps
Affiliation:1. Institute of Statistics, RWTH Aachen University, D-52056 Aachen, Germanybedbur@stochastik.rwth-aachen.de;3. Department of Quantitative Economics, Maastricht University, PO Box 616, NL-6200 MD Maastricht, The Netherlands;4. Institute of Statistics, RWTH Aachen University, D-52056 Aachen, Germany
Abstract:
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.
Keywords:order statistic  sequential order statistic  k-out-of-n system  conditional proportional hazard rate  record value  Pfeifer record value
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