In this paper, we develop a Neyman-type smooth test for the serial dependence of unobservable generalized errors. Our test is "nuisance parameter-free" in the sense that model parameter estimation uncertainty has no impact on the limit distribution of the test statistic.

This paper was written to mark the 50th anniversary of Neyman and Scott's Econometrica paper de"ning the incidental parameter problem. It surveys the history both of the paper and of the problem in the statistics and econometrics literature. ( 2000 Elsevier Science S.A. All rights reserved. JEL classixcation: B23; C10

In hypotheses testing, such as other statistical problems, we may confront imprecise concepts. One case is a situation in which both hypotheses and observations are imprecise. In this paper, we redefine some concepts about fuzzy hypotheses testing, and then we give the Neyman-Pearson lemma for fuzzy hypotheses testing with fuzzy observations. Finally, we give some applied examples. Mathematics ...

In this paper, the design of optimal schemes for detecting deterministic narrowband signals with unknown parameters in correlated interference modelled by the recently developed GBK distribution is considered. Theoretical derivations of an optimal detector, in the Neyman-Pearson sense, are given for the case where the signal amplitude and phase are unknown. The performance of the detector is th...

We have developed biometric fusion technique based on stochastic theory. The suggested method is a robust adaptation of the Neyman-Pearson technique to the specifics of biometrics. The method makes possible to achieve almost optimal performance as measured by the ROC curve.