In this paper, we consider the detection problem with intermittent observations, due to the unreliable shared communication link between local sensors and the fusion center. Detection performance is analyzed using Neyman-Pearson criterion of maximizing the probability of detection, for a given probability of false alarm. The detector performance is compared, with and without intermittent observ...

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...

For some populations there may be two or more stratifying criteria that are desirable in the sample design. Multi-way stratification allows increased precision of estimates of each of the variables whose precision is increased by typical univariate estimators corresponding to singlecriteria designs. The sample need not be allocated to every multi-way population cell induced by a set of single-c...

in the analysis of spatial point patterns, complete spatial randomness (csr) hypothesis,which is a restriction of a homogenous poisson process to study region a, operates as a dividinghypothesis between “regular” and “aggregated” patterns. meanwhile, many alternatives to csr inaggregated patterns are extensions of homogenous poisson processes themselves. therefore, when thecsr hypothesis is rej...

A procedure for finding the Neyman–Pearson optimum distributed sensor detectors for cases with statistically dependent observations is described. This is the first 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 s...

Akaike's criterion is used to test composite hypotheses ; for example to determine the order of AR models. A modiication is presented to test composite hypotheses given an upper-bound on the error of the rst kind (Neyman-Pearson). The presented theory is applied to AR order estimation and veriied by simulations. The experimental results are so good that we consider the AR order estimation probl...

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 studies the Generalized Neyman–Pearson (GNP) optimality of empirical likelihood-based tests for parameter hypotheses. The GNP optimality focuses on the large deviation errors of tests, i.e., the convergence rates of the type I and II error probabilities under fixed alternatives. We derive (i) the GNP optimality of the empirical likelihood criterion (ELC) test against all alternatives...