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Elements of stochastic modelling / Konstantin Borovkov.

By: Material type: TextTextPublication details: Singapore : World Scientific, ©2014.Edition: 2nd edDescription: xvi, 482 pages : illustrations ; 24 cmISBN:
  • 9789814571159 (hardcover)
Subject(s): DDC classification:
  • 519.23 23 B736
Contents:
1. Introduction -- 2. Basics of probability theory -- 3. Markov chains -- 4. Markov decision processes -- 5. The exponential distribution and poisson process -- 6. Jump Markov processes -- 7. Elements of queueing theory -- 8. Elements of renewal theroy -- 9. Elements of time series -- 10. Elements of simulation -- 11. Martingales and stochastic calculus -- 12. Diffusion processes -- 13. Elements of mathematical finance.
Summary: This is the expanded second edition of a successful textbook that provides a broad introduction to important areas of stochastic modelling. The original text was developed from lecture notes for a one-semester course for third-year science and actuarial students at the University of Melbourne. It reviewed the basics of probability theory and then covered the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time series and simulation.
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Includes bibliographical references and index.

1. Introduction --
2. Basics of probability theory --
3. Markov chains --
4. Markov decision processes --
5. The exponential distribution and poisson process --
6. Jump Markov processes --
7. Elements of queueing theory --
8. Elements of renewal theroy --
9. Elements of time series --
10. Elements of simulation --
11. Martingales and stochastic calculus --
12. Diffusion processes --
13. Elements of mathematical finance.

This is the expanded second edition of a successful textbook that provides a broad introduction to important areas of stochastic modelling. The original text was developed from lecture notes for a one-semester course for third-year science and actuarial students at the University of Melbourne. It reviewed the basics of probability theory and then covered the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time series and simulation.

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