In light of the information measures introduced in Part I, a generalized version of the Asymp-totic Equipartition Property (AEP) is proved. General xed-length data compaction and data compression (source coding) theorems for arbitrary nite-alphabet sources are also established. Finally, the general expression of the Neyman-Pearson type-II error exponent subject to upper bounds on the type-I err...

We present a new analysis for the combination of binary classifiers. Our analysis makes use of the Neyman-Pearson lemma as a theoretical basis to analyze combinations of classifiers. We give a method for finding the optimal decision rule for a combination of classifiers and prove that it has the optimal ROC curve. We show how our method generalizes and improves previous work on combining classi...

On After-Trial Criticisms of Neyman-Pearson Theory of Statistics Author(s): Deborah G. Mayo Source: PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, Vol. 1982, Volume One: Contributed Papers (1982), pp. 145-158 Published by: The University of Chicago Press on behalf of the Philosophy of Science Association Stable URL: http://www.jstor.org/stable/192663 Accessed...

This material is designed to introduces basic concepts and fundamental theory of mathematical statistics. A review of basic concepts will include likelihood functions, sufficient statistics, and exponential family of distributions. Then point estimation will be discussed, including minimum variance unbiased estimates, Cramér-Rao inequality, maximum likelihood estimates and asymptotic theory. To...

We present and derive the asymptotic properties of a certain Neyman-Pearson test, relevant for 14 problems concerning discrimination between two competing models. We then study an application in which this test is used to assess the efficacy of designs, the purpose of which is to aid in discriminating 16 between two nonlinear regression models. AMS Subject Classification: Primary: 62F03; 62F05....

A procedure for nding the Neyman-Pearson optimum distributed sensor detectors for cases with statistically dependent observations is described. This is the rst valid procedure we have seen for this case. This procedure is based on a Theorem proven in this paper. These results clarify and correct a number of possibly misleading discussions in the existing literature. Cases with networks of senso...

This paper address the issue of structural change, caused by ice accretion, on UAVs by utilising a Neyman Pearson (NP) based statistical change detection approach, for the identification of structural changes of fixed wing UAV airfoils. A structural analysis is performed on the nonlinear aircraft system and residuals are generated, where a generalised likelihood ratio test is applied to detect ...

Abstract Flight safety is an integral part of air transportation. accidents are highly unlikely to appear but most them caused by the human factor. The aircrew training system for abnormal operations relies on integrated aircraft simulator-based exercises. Crew needs be trained not degrade piloting technique quality when facing increased psychophysiological tension. Therefore, methods evaluatin...

Population limitation is a fundamental tenet of ecology, but the relative roles of exogenous and endogenous mechanisms remain unquantified for most species. Here we used multi-model inference (MMI), a form of model averaging, based on information theory (Akaike's Information Criterion) to evaluate the relative strength of evidence for density-dependent and density-independent population dynamic...

We consider the problem of distributed binary hypothesis testing with independent identical sensors. It is well known that for this problem the optimal sensor rules are a likelihood ratio threshold tests and the optimal fusion rule is a K-out-of-N rule [1]. Under the Bayesian criterion, we show that for a fixed K-out-of-N fusion rule, the probability of error is a quasiconvex function of the li...