Current molecular methods of species delimitation are limited by the types of species delimitation models and scenarios that can be tested. Bayes factors allow for more flexibility in testing non-nested species delimitation models and hypotheses of individual assignment to alternative lineages. Here, we examined the efficacy of Bayes factors in delimiting species through simulations and empiric...

We propose a class of estimators of the Bayes factor which is based on an extension of the bridge sampling identity of Meng & Wong (1996) and makes use of the output of the reversible jump algorithm of Green (1995). Within this class we give the optimal estimator and also a suboptimal one which may be simply computed on the basis of the acceptance probabilities used within the reversible jump a...

The article is concerned with analysis of failure rate (shape parameter) under the Topp Leone distribution using a Bayesian framework. Different loss functions and a couple of noninformative priors have been assumed for posterior estimation. The posterior predictive distributions have also been derived. A simulation study has been carried to compare the performance of different estimators. A re...

Classical approaches to estimating the rate of occurrence of events perform poorly when data are few. Maximum Likelihood Estimators result in overly optimistic point estimates of zero for situations where there have been no events. Alternative empirical based approaches have been proposed based on median estimators or noninformative prior distributions. While these alternatives offer an improve...

To study lifetimes of certain engineering processes, a lifetime model which can accommodate the nature of such processes is desired. The mixture models of underlying lifetime distributions are intuitively more appropriate and appealing to model the heterogeneous nature of process as compared to simple models. This paper is about studying a 3-component mixture of the Rayleigh distributionsin Bay...

In this paper, we consider the Bayesian estimation of parameters in the proportional hazards model of random censorship for the Weibull distribution under different asymmetric loss functions. It is well-known for the Weibull distribution that a joint conjugate prior on the parameters does not exist; we use both the informative and noninformative priors on the model parameters. Bayes estimates u...

This dissertation aims at applying the novel formalism of Random Set Theory (RST) to some problems in communication theory: tracking of mobile users that are continuously entering and leaving a wireless network and tracking of abruptly time-varying channel where multipath components are free to appear and disappear. RST allows to solve both problems in an unified framework through Bayes recursi...

A complete algorithm is presented for the sharpening of imprecise information, based on the methodology of kernel estimators and the Bayes decision rule, including conditioning factors. The use of the Bayes rule with a nonsymmetrical loss function enables the inclusion of different results of an underand overestimation of a sharp value (real number), as well as minimizing potential losses. A co...