Markov Chains: Models, Algorithms and Applications

摘要: This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end-of-chapter exercises, focus on management science, applications the models, examples in financial risk modeling data. book consists eight chapters. Chapter 1 gives brief introduction to classical theory both discrete continuous time chains. The relationship between chains finite states matrix will also be highlighted. Some iterative methods for solving linear systems introduced finding stationary distribution chain. chapter then covers basic theories algorithms hidden models (HMMs) decision processes (MDPs). 2 discusses model queueing chain computing PageRank, ranking websites Internet. 3 studies Markovian manufacturing re-manufacturing presents closed form solutions fast numerical captured systems. In 4, authors present simple (HMM) estimating parameters. An application HMM customer classification is presented. 5 lifetime values. Customer Lifetime Values (CLV) an important concept quantity marketing management. approach based calculation CLV using real 6 considers higher-order particularly class parsimonious models. Efficient estimation parameters programming are Contemporary research results demand predictions, inventory control measurement 7, multivariate introduced. Again, efficient policy credit ratings data discussed. Finally, 8 re-visits interest rates, default aimed at senior undergraduate students, postgraduate professionals, practitioners, researchers applied mathematics, computational operational research, science finance, who interested formulation computation networks, related topics. Readers expected have some knowledge probability theory, theory.