MCMC approach to modelling queuing systems

A MCMC Approach to Hierarchical Mixture Modelling

There are many hierarchical clustering algorithms available, but these lack a firm statistical basis. Here we set up a hierarchical probabilistic mixture model, where data is generated in a hierarchical tree-structured manner. Markov chain Monte Carlo (MCMC) methods are demonstrated which can be used to sample from the posterior distribution over trees containing variable numbers of hidden units.

Dynamic Probabilistic Networks for Modelling and Identifying Dynamic Systems: a MCMC Approach

The Application of Phase Type Distributions for Modelling Queuing Systems

Queuing models are important tools for studying the performance of complex systems, but despite the substantial queuing theory literature, it is often necessary to use approximations in the case the system is nonmarkovian. Phase type distribution is by now indispensable tool in creation of queuing system models. The purpose of this paper is to suggest a method and software for evaluating queuin...

non-corrective approach to pronunciation

the aim of this study has been to find answers for the following questions: 1. what is the effect of immediate correction on students pronunciation errors? 2. what would be the effect of teaching the more rgular patterns of english pronunciation? 3. is there any significant difference between the two methods of dealing with pronuciation errore, i. e., correction and the teaching of the regular ...

An Approach to Modelling Legacy Enterprise Systems

The reclamation and redevelopment of software "brownfield sites" requires a multi-layered understanding of the domain in which the enterprise system lives. A further dimension is added to the interconnectivity of the domain knowledge when the evolution of the system requires the migration of existing services to a web-based system and the creation of new value-added services. Where the enterpri...