Physical Sciences and Mathematics Commons^™

Supervised Classification Using Copula And Mixture Copula, Sumen Sen

Mathematics & Statistics Theses & Dissertations

Statistical classification is a field of study that has developed significantly after 1960's. This research has a vast area of applications. For example, pattern recognition has been proposed for automatic character recognition, medical diagnostic and most recently in data mining. Classical discrimination rule assumes normality. However in many situations, this assumption is often questionable. In fact for some data, the pattern vector is a mixture of discrete and continuous random variables. In this dissertation, we use copula densities to model class conditional distributions. Such types of densities are useful when the marginal densities of a pattern vector are not normally …

Single Row Routing: Theoretical And Experimental Performance Evaluation, And New Heuristic Development, David A. Hysom

Computer Science Theses & Dissertations

The Single Row Routing Problem (SRRP) is an abstraction arising from real-world multilayer routing concerns. While NP-Complete, development of efficient SRRP routing heuristics are of vital concern to VLSI design. Previously, researchers have introduced various heuristics for SRRP; however, a comprehensive examination of SRRP behavior has been lacking.

We are particularly concerned with the street-congestion minimization constraint, which is agreed to be the constraint of greatest interest to industry. Several theorems stating lower bounds on street congestion are known. We show that these bounds are not tight in general, and argue they may be in error by at least 50% …

Estimating The Parameters Of Truncated Distributions, Mukul Mohan Mittal

Mathematics & Statistics Theses & Dissertations

The problem considered here is the estimation of the parameters of some special truncated distributions. If the sample observations are restricted to the interval {O, T} with T known, then it is well known in the literature that the method of maximum likelihood fails to provide a finite estimate, for the mean of an exponential distribution, whenever the sample mean is greater than T/2 (Deemer and Votaw, 1955, Ann. Math. Statist. 26, 498-504). Not so well known is the nonexistence of the maximum likelihood estimator (m.l.e.), under certain conditions, for the scale parameter of a gamma distribution from a truncated …