The Neyman-Pearson (NP) paradigm in binary classification treats type I and type II errors with different priorities. It seeks classifiers that minimize type II error, subject to a type I error constraint under a user specified level α. In this paper, plug-in classifiers are developed under the NP paradigm. Based on the fundamental Neyman-Pearson Lemma, we propose two related plug-in classifier...

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II ...

This paper compares and investigates the generalised Neyman smooth test, its components, and the classical chi-squared test with a variety of equiprobable classes. Each test is evaluated in terms of its power to reject a wavelike alternative to the uniform distribution, chosen to quantify the complexity of the alternative. Results indicate that if broadly focused tests (rather than strongly dir...

In current scenario, the demand for wireless communication is increasing drastically. A wireless system has number of advantages over its wired counterpart including allowing a communication link to be set up quickly without the difficulty and expense of installing data transmission lines. The wireless communications industry has experienced an explosive growth in the last decade. One of the mo...

We give a combinatorial description of the toric ideal invariants Cavender-Farris-Neyman model with molecular clock (CFN-MC) on rooted binary phylogenetic tree and prove results about polytope associated to this ideal. Key polyhedral structure include that number vertices is Fibonacci number, facets can be described using “cluster” underlying tree, volume equal an Euler zig-zag number. The CFN-...

The theory of distributed detection is receiving a lot of attention. A common assumption used in previous studies is the conditional independence of the observations. In this paper, the optimization of local decision rules for distributed detection networks with correlated observations is considered. We focus on presenting the detection theory for parallel distributed detection networks with fi...

We give an axiomatization of the Aumann-Shapley cost-sharing method in the discrete case by means of monotonicity and no merging or splitting (Sprumont, 2005 [16]). Monotonicity has not yet been employed to characterize this method in such a case, unlike the case in which goods are perfectly divisible, for which Monderer and Neyman (1988) [10] and Young (1985) [19] characterize the Aumann-Shapl...