Markov chain models: computations and applications

Session 3 Invited Lectures: 3.8 Group 8: Numerical Analysis, Scientific Computing, Imaging, Bio-Mathematics, Machine Learning, Probability, Statistical Theory and Method, Application of Statistics -- 45 Minutes TalkMarkov chain models are popular mathematical tools for studying many different kinds of real world systems such as queueing networks (continuous time) and categorical data sequences (discrete time). In this talk, I shall first present some efficient numerical algorithms for solving Markovian queueing networks. I shall then introduce some other parsimonious high-order and multivariate Markov chain models for categorical sequences with applications. Efficient estimation methods for solving the model parameters will also be discussed. Practical problems and numerical examples will then be given to demonstrate the effectiveness of our proposed models