Mathematical Techniques of Applied Probability
eBook - PDF

Mathematical Techniques of Applied Probability

Discrete Time Models: Basic Theory

  1. 254 pages
  2. English
  3. PDF
  4. Only available on web
eBook - PDF

Mathematical Techniques of Applied Probability

Discrete Time Models: Basic Theory

Book details
Table of contents
Citations

About This Book

Mathematical Techniques of Applied Probability, Volume 1: Discrete Time Models: Basic Theory provides information pertinent to the basic theory of discrete time models. This book introduces the tools of generating functions and matrix theory to facilitate a detailed study of such models. Organized into five chapters, this volume begins with an overview of the elementary theory of probability for discrete random variables. This text then reviews the concepts of convergence, absolute convergence, uniform convergence, continuity, differentiation, and integration. Other chapters consider the occurrence of general patterns of successes and failures in Bernoulli trials. This book discusses as well the matrix theory, which is used in the study of stochastic processes, particularly in the analysis of the behavior of Markov chains. The final chapter deals with the properties of a special class of discrete time chains. This book is a valuable resource for students and teachers.

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Yes, you can access Mathematical Techniques of Applied Probability by Jeffrey J. Hunter, J. William Schmidt in PDF and/or ePUB format, as well as other popular books in Matemáticas & Probabilidad y estadística. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2014
ISBN
9781483263885
Topic
Matemáticas
Subtopic
Probabilidad y estadística

Table of contents

  1. Front Cover
  2. Discrete Time Models: Basic Theory
  3. Copyright Page
  4. Table of Contents
  5. Preface
  6. Acknowledgments
  7. Contents of Volume 2
  8. Chapter 1. Basic Probability
  9. Chapter 2. Generating Functions
  10. Chapter 3. Recurrent Event Theory
  11. Chapter 4. Matrix Techniques
  12. Chapter 5. Markov Chains in Discrete Time—Basic Theory
  13. References
  14. Index