An Advanced Course in Probability and Stochastic Processes
eBook - PDF

An Advanced Course in Probability and Stochastic Processes

  1. 384 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

An Advanced Course in Probability and Stochastic Processes

About this book

An Advanced Course in Probability and Stochastic Processes provides a modern and rigorous treatment of probability theory and stochastic processes at an upper undergraduate and graduate level. Starting with the foundations of measure theory, this book introduces the key concepts of probability theory in an accessible way, providing full proofs and extensive examples and illustrations. Fundamental stochastic processes such as Gaussian processes, Poisson random measures, Lévy processes, Markov processes, and Itô processes are presented and explored in considerable depth, showcasing their many interconnections. Special attention is paid to martingales and the Wiener process and their central role in the treatment of stochastic integrals and stochastic calculus. This book includes many exercises, designed to test and challenge the reader and expand their skillset. An Advanced Course in Probability and Stochastic Processes is meant for students and researchers who have a solid mathematical background and who have had prior exposure to elementary probability and stochastic processes.

Key Features:

  • Focus on mathematical understanding
  • Rigorous and self-contained
  • Accessible and comprehensive
  • High-quality illustrations
  • Includes essential simulation algorithms
  • Extensive list of exercises and worked-out examples
  • Elegant and consistent notation

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Yes, you can access An Advanced Course in Probability and Stochastic Processes by Dirk P. Kroese,Zdravko Botev in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Contents
  7. Notation
  8. 1. Measure Theory
  9. 2. Probability
  10. 3. Convergence
  11. 4. Conditioning
  12. 5. Martingales
  13. 6. Wiener and Brownian Motion Processes
  14. 7. Itô Calculus
  15. A. Selected Solutions
  16. B. Function Spaces
  17. C. Existence of the Lebesgue Measure
  18. Bibliography
  19. Index