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Essentials of Stochastic Processes

Essentials of Stochastic Processes


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About the Book

1) Markov Chains1.1 Definitions and Examples1.2 Multistep Transition Probabilities1.3 Classification of States 1.4 Stationary Distributions1.4.1 Doubly stochastic chains1.5 Detailed balance condition1.5.1 Reversibility 1.5.2 The Metropolis-Hastings algorithm1.5.3 Kolmogorow cycle condition 1.6 Limit Behavior 1.7 Returns to a fixed state 1.8 Proof of the convergence theorem*1.9 Exit Distributions 1.10 Exit Times1.11 Infinite State Spaces* 1.12 Chapter Summary1.13 Exercises
2) Poisson Processes 2.1 Exponential Distribution 2.2 Defining the Poisson Process2.2.1 Constructing the Poisson Process2.2.2 More realistic models2.3 Compound Poisson Processes 2.4 Transformations2.4.1 Thinning 2.4.2 Superposition2.4.3 Conditioning2.5 Chapter Summary2.6 Exercises
3) Renewal Processes3.1 Laws of Large Numbers3.2 Applications to Queueing Theory3.2.1 GI/G/1 queue3.2.2 Cost equations 3.2.3 M/G/1 queue3.3 Age and Residual Life*3.3.1 Discrete case3.3.2 General case 3.4 Chapter Summary 3.5 Exercises
4) Continuous Time Markov Chains 4.1 Definitions and Examples4.2 Computing the Transition Probability4.2.1 Branching Processes 4.3 Limiting Behavior 4.3.1 Detailed balance condition 4.4 Exit Distributions and Exit Times 4.5 Markovian Queues 4.5.1 Single server queues4.5.2 Multiple servers4.5.3 Departure Processes 4.6 Queueing Networks*4.7 Chapter Summary4.8 Exercises
5) Martingales 5.1 Conditional Expectation 5.2 Examples5.3 Gambling Strategies, Stopping Times 5.4 Applications 5.4.1 Exit distributions5.4.2 Exit times 5.4.3 Extinction and ruin probabilities5.4.4 Positive recurrence of the GI/G/1 queue*5.5 Exercises
6) Mathematical Finance6.1 Two Simple Examples6.2 Binomial Model 6.3 Concrete Examples 6.4 American Options6.5 Black-Scholes formula6.6 Calls and Puts6.7 Exercises
A) Review of Probability A.1 Probabilities, Independence A.2 Random Variables, Distributions A.3 Expected Value, MomentsA.4 Integration to the Limit

About the Author:

Richard Durrett received his Ph.D. in Operations Research from Stanford in 1976. He taught at the UCLA mathematics department for 9 years and at Cornell for 25 years before moving to Duke in 2010. He is author of 8 books and more than 200 journal articles and has supervised more that 45 Ph.D. students. He is a member of the National Academy of Science. Most of his current research concerns the applications of probability to biology: ecology, genetics, and most recently cancer.


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Product Details
  • ISBN-13: 9783319833316
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Height: 234 mm
  • No of Pages: 275
  • Series Title: Springer Texts in Statistics
  • Weight: 458 gr
  • ISBN-10: 3319833316
  • Publisher Date: 22 Apr 2018
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 15 mm
  • Width: 156 mm


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Essentials of Stochastic Processes
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