Markov chains: models, algorithms and applications Ching, W. K.
Series: International series in operations research & management science, Vol. 189Publication details: 2013 Springer New YorkEdition: 2nd edDescription: xvi, 243 pISBN:- 9781461463115
- 658.40301 C4M2
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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Ahmedabad General Stacks | Non-fiction | 658.40301 C4M2 (Browse shelf(Opens below)) | Available | 179406 |
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658.403 C6B8 Bulletproof problem solving: the one skill that changes everything | 658.403 R2B8 Business analytics: an application focus | 658.403 S8P7 Professionals making judgments: the professional skill of valuing and assessing | 658.40301 C4M2 Markov chains: models, algorithms and applications | 658.40301 G2C6 Complementarity modeling in energy markets | 658.40301 O7 Optimal financial decision making under uncertainty | 658.40301 Z4S8 Supply chain finance: integrating operations and finance in global supply chains |
This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end-of-chapter exercises, a new focus on management science, new applications of the models, and new examples with applications in financial risk management and modeling of financial data.
This book consists of eight chapters. Chapter 1 gives a brief introduction to the classical theory on both discrete and continuous time Markov chains. The relationship between Markov chains of finite states and matrix theory will also be highlighted. Some classical iterative methods for solving linear systems will be introduced for finding the stationary distribution of a Markov chain. The chapter then covers the basic theories and algorithms for hidden Markov models (HMMs) and Markov decision processes (MDPs).
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