rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Markov Chains
    sub title: Models, Algorithms and Applications
  name:
    name part: Ching, Wai-Ki.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Huang, Ximin.
    role:
      role term: author.
  name:
    name part: Ng, Michael K.
    role:
      role term: author.
  name:
    name part: Siu, Tak-Kuen.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2013
    edition: 2nd ed. 2013.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 243 p. online resource.
  abstract: 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 co…
  table of contents: Introduction -- Manufacturing and Re-manufacturing Systems -- A Hidden Markov Model for Customer Classification -- Markov Decision Processes for Customer Lifetime Value -- Higher-order Markov Chains -- Multivariate Markov Chains -- Hidden Markov Chains.
  note: by Wai-Ki Ching, Ximin Huang, Michael K. Ng, Tak-Kuen Siu.
  subject:
    topic: Business
  subject:
    topic: Operations research
  subject:
    topic: Decision making
  subject:
    topic: Management science
  subject:
    topic: Probabilities
  subject:
    topic: Business and Management
  subject:
    topic: Operation Research/Decision Theory
  subject:
    topic: Operations Research, Management Science
  subject:
    topic: Probability Theory and Stochastic Processes
  classification: HD30.23
  classification: 658.40301
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: International Series in Operations Research & Management Science, 189
  identifier: 9781461463122
  identifier: http://dx.doi.org/10.1007/978-1-4614-6312-2
  record info:
    record creation date: 130327
    record change date: 20151204141829.0
    record identifier: 978-1-4614-6312-2