Improving the efficiency and robustness of nested sampling using posterior repartitioning

assessment of the efficiency of s.p.g.c refineries using network dea

data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...

on the relationship between using discourse markers and the quality of expository and argumentative academic writing of iranian english majors

the aim of the present study was to investigate the frequency and the type of discourse markers used in the argumentative and expository writings of iranian efl learners and the differences between these text features in the two essay genres. the study also aimed at examining the influence of the use of discourse markers on the participants’ writing quality. to this end the discourse markers us...

Performance and Robustness Analysis of Co-Prime and Nested Sampling

Title of Thesis: Performance and Robustness Analysis of Co-Prime and Nested Sampling Ali Koochakzadeh, Master of Science, 2016 Thesis Directed By: Professor Piya Pal Department of Electrical and Computer Engineering Coprime and nested sampling are well known deterministic sampling techniques that operate at rates significantly lower than the Nyquist rate, and yet allow perfect reconstruction of...

Posterior sampling with improved efficiency

The Markov Chain Monte Carlo (MCMC) technique provides a means to generate a random sequence of model realizations that sample the posterior probability distribution of a Bayesian analysis. That sequence may be used to make inferences about the model uncertainties that derive from measurement uncertainties. This paper presents an approach to improving the efficiency of the Metropolis approach t...

Improving the Efficiency and Robustness of Intrusion Detection Systems