b a c k g r o u n d & aim: the aim of the current study was to investigate the advantages of bayesian method in comparison to traditional methods to detect best antioxidant in freezing of human male gametes. methods  &  materials:   semen  samples  were  obtained  from  40  men  whose  sperm  had  normal criteria. a part of each sample was separated without antioxidant  as fresh and the remaini...

we propose to use a mathematical method based on stochastic comparisons of markov chains in order to derive performance indice bounds‎. ‎the main goal of this paper is to investigate various monotonicity properties of a single server retrial queue with first-come-first-served (fcfs) orbit and general retrial times using the stochastic ordering techniques‎.

Bayesian networks are a popular representation of asymmetric (for example causal) relationships between random variables. Markov random fields (MRFs) are a complementary model of symmetric relationships used in computer vision, spatial modeling, and social and gene expression networks. A chain graph model under the Lauritzen-Wermuth-Frydenberg interpretation (hereafter a chain graph model) gene...

Markov chain models had proved to be useful tools in many fields, such as physics, chemistry, information sciences, economics, finances, mathematical biology, social sciences, and statistics for analyzing data. A discrete time Markov chain is often used as a statistical model from a random physical process to fit the observed data. A time-homogeneous Markov chain is a process that each transiti...

the problem we investigate deals with the optimal assignment of resources to the activities of a stochastic project network. we seek to minimize the expected cost of the project include sum of resource utilization costs and lateness costs. we assume that the work content required by the activities follows an exponential distribution. the decision variables of the model are the allocated resourc...

This article concerns the study of the asymptotic properties of the maximum likelihood estimator (MLE) for the general hidden semi-Markov model (HSMM) with backward recurrence time dependence. By transforming the general HSMM into a general hidden Markov model, we prove that under some regularity conditions, the MLE is strongly consistent and asymptotically normal. We also provide useful expres...

We analyze the convergence to stationarity of a simple nonreversible Markov chain that serves as a model for several nonreversible Markov chain sampling methods that are used in practice. Our theoretical and numerical results show that nonreversibility can indeed lead to improvements over the diffusive behavior of simple Markov chain sampling schemes. The analysis uses both probabilistic techni...

Fear of increasing prices and concern about climate change are motivating residential power conservation efforts. We investigate the effectiveness of several unsupervised disaggregation methods on low frequency power measurements collected in real homes. Specifically, we consider variants of the factorial hidden Markov model. Our results indicate that a conditional factorial hidden semi-Markov ...