Markov Chains

Models, Algorithms and Applications

Business & Finance, Management & Leadership, Operations Research, Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book Markov Chains by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu, Springer US
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu ISBN: 9781461463122
Publisher: Springer US Publication: March 27, 2013
Imprint: Springer Language: English
Author: Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
ISBN: 9781461463122
Publisher: Springer US
Publication: March 27, 2013
Imprint: Springer
Language: English

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).

Chapter 2 discusses the applications of continuous time Markov chains to model queueing systems and discrete time Markov chain for computing the PageRank, the ranking of websites on the Internet. Chapter 3 studies Markovian models for manufacturing and re-manufacturing systems and presents closed form solutions and fast numerical algorithms for solving the captured systems. In Chapter 4, the authors present a simple hidden Markov model (HMM) with fast numerical algorithms for estimating the model parameters. An application of the HMM for customer classification is also presented.

Chapter 5 discusses Markov decision processes for customer lifetime values. Customer Lifetime Values (CLV) is an important concept and quantity in marketing management. The authors present an approach based on Markov decision processes for the calculation of CLV using real data.

Chapter 6 considers higher-order Markov chain models, particularly a class of parsimonious higher-order Markov chain models. Efficient estimation methods for model parameters based on linear programming are presented. Contemporary research results on applications to demand predictions, inventory control and financial risk measurement are also presented. In Chapter 7, a class of parsimonious multivariate Markov models is introduced. Again, efficient estimation methods based on linear programming are presented. Applications to demand predictions, inventory control policy and modeling credit ratings data are discussed. Finally, Chapter 8 re-visits hidden Markov models, and the authors present a new class of hidden Markov models with efficient algorithms for estimating the model parameters. Applications to modeling interest rates, credit ratings and default data are discussed.
 
This book is aimed at senior undergraduate students, postgraduate students, professionals, practitioners, and researchers in applied mathematics, computational science, operational research, management science and finance, who are interested in the formulation and computation of queueing networks, Markov chain models and related topics. Readers are expected to have some basic knowledge of probability theory, Markov processes and matrix theory.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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).

Chapter 2 discusses the applications of continuous time Markov chains to model queueing systems and discrete time Markov chain for computing the PageRank, the ranking of websites on the Internet. Chapter 3 studies Markovian models for manufacturing and re-manufacturing systems and presents closed form solutions and fast numerical algorithms for solving the captured systems. In Chapter 4, the authors present a simple hidden Markov model (HMM) with fast numerical algorithms for estimating the model parameters. An application of the HMM for customer classification is also presented.

Chapter 5 discusses Markov decision processes for customer lifetime values. Customer Lifetime Values (CLV) is an important concept and quantity in marketing management. The authors present an approach based on Markov decision processes for the calculation of CLV using real data.

Chapter 6 considers higher-order Markov chain models, particularly a class of parsimonious higher-order Markov chain models. Efficient estimation methods for model parameters based on linear programming are presented. Contemporary research results on applications to demand predictions, inventory control and financial risk measurement are also presented. In Chapter 7, a class of parsimonious multivariate Markov models is introduced. Again, efficient estimation methods based on linear programming are presented. Applications to demand predictions, inventory control policy and modeling credit ratings data are discussed. Finally, Chapter 8 re-visits hidden Markov models, and the authors present a new class of hidden Markov models with efficient algorithms for estimating the model parameters. Applications to modeling interest rates, credit ratings and default data are discussed.
 
This book is aimed at senior undergraduate students, postgraduate students, professionals, practitioners, and researchers in applied mathematics, computational science, operational research, management science and finance, who are interested in the formulation and computation of queueing networks, Markov chain models and related topics. Readers are expected to have some basic knowledge of probability theory, Markov processes and matrix theory.

More books from Springer US

Cover of the book Apoptosis in Cardiac Biology by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Children and Disasters by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Drug Resistance in Cancer Therapy by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Dielectric Polymer Nanocomposites by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Model-Based Reasoning by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Social Referencing and the Social Construction of Reality in Infancy by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Progress in Sexology by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Hormone Signaling by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Congenital Anomalies of the Upper Extremity by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Essays in Production, Project Planning and Scheduling by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Highly Linear Integrated Wideband Amplifiers by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Stopping Domestic Violence by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book The Biology of Alcoholism by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Teaching Interpersonal Skills by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
Cover of the book Handbook of Biomedical Imaging by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy