A First Course in Stochastic Processes
eBook - PDF

A First Course in Stochastic Processes

  1. 514 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

A First Course in Stochastic Processes

About this book

A First Course in Stochastic Processes focuses on several principal areas of stochastic processes and the diversity of applications of stochastic processes, including Markov chains, Brownian motion, and Poisson processes. The publication first takes a look at the elements of stochastic processes, Markov chains, and the basic limit theorem of Markov chains and applications. Discussions focus on criteria for recurrence, absorption probabilities, discrete renewal equation, classification of states of a Markov chain, and review of basic terminologies and properties of random variables and distribution functions. The text then examines algebraic methods in Markov chains and ratio theorems of transition probabilities and applications. The manuscript elaborates on the sums of independent random variables as a Markov chain, classical examples of continuous time Markov chains, and continuous time Markov chains. Topics include differentiability properties of transition probabilities, birth and death processes with absorbing states, general pure birth processes and Poisson processes, and recurrence properties of sums of independent random variables. The book then ponders on Brownian motion, compounding stochastic processes, and deterministic and stochastic genetic and ecological processes. The publication is a valuable source of information for readers interested in stochastic processes.

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Yes, you can access A First Course in Stochastic Processes by Samuel Karlin in PDF and/or ePUB format, as well as other popular books in Mathematics & Applied Mathematics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Front Cover
  2. A First Course in Stochastic Processes
  3. Copyright Page
  4. Table of Contents
  5. Preface
  6. Chapter 1. ELEMENTS OF STOCHASTIC PROCESSES
  7. Chapter 2. MARKOV CHAINS
  8. Chapter 3. THE BASIC LIMIT THEOREM OF MARKOV CHAINS AND APPLICATIONS
  9. Chapter 4. ALGEBRAIC METHODS IN MARKOV CHAINS
  10. Chapter 5. RATIO THEOREMS OF TRANSITION PROBABILITIES AND APPLICATIONS
  11. Chapter 6. SUMS OF INDEPENDENT RANDOM VARIABLES AS A MARKOV CHAIN
  12. Chapter 7. CLASSICAL EXAMPLES OF CONTINUOUS TIME MARKOV CHAINS
  13. Chapter 8. CONTINUOUS TIME MARKOV CHAINS
  14. Chapter 9. ORDER STATISTICS, POISSON PROCESSES, AND APPLICATIONS
  15. Chapter 10. BROWNIAN MOTION
  16. Chapter 11. BRANCHING PROCESSES
  17. Chapter 12. COMPOUNDING STOCHASTIC PROCESSES
  18. Chapter 13. DETERMINISTIC AND STOCHASTIC GENETO AND ECOLOGICAL PROCESSES
  19. Chapter 14. QUEUEING PROCESSES
  20. APPENDIX. REVIEW OF MATRIX ANALYSIS
  21. MISCELLANEOUS PROBLEMS
  22. INDEX