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A Course in Stochastic Processes

Stochastic Models and Statistical Inference

  • Denis Bosq
  • Hung T. Nguyen

Part of the Theory and Decision Library book series (TDLB, volume 34)

Table of contents

  1. Front Matter
    Pages i-x
  2. Denis Bosq, Hung T. Nguyen
    Pages 1-32
  3. Denis Bosq, Hung T. Nguyen
    Pages 33-44
  4. Denis Bosq, Hung T. Nguyen
    Pages 45-77
  5. Denis Bosq, Hung T. Nguyen
    Pages 79-94
  6. Denis Bosq, Hung T. Nguyen
    Pages 95-116
  7. Denis Bosq, Hung T. Nguyen
    Pages 117-146
  8. Denis Bosq, Hung T. Nguyen
    Pages 147-169
  9. Denis Bosq, Hung T. Nguyen
    Pages 171-188
  10. Denis Bosq, Hung T. Nguyen
    Pages 189-203
  11. Denis Bosq, Hung T. Nguyen
    Pages 205-217
  12. Denis Bosq, Hung T. Nguyen
    Pages 219-232
  13. Denis Bosq, Hung T. Nguyen
    Pages 233-253
  14. Denis Bosq, Hung T. Nguyen
    Pages 255-269
  15. Denis Bosq, Hung T. Nguyen
    Pages 271-285
  16. Denis Bosq, Hung T. Nguyen
    Pages 287-298
  17. Back Matter
    Pages 299-354

About this book

Introduction

This text is an Elementary Introduction to Stochastic Processes in discrete and continuous time with an initiation of the statistical inference. The material is standard and classical for a first course in Stochastic Processes at the senior/graduate level (lessons 1-12). To provide students with a view of statistics of stochastic processes, three lessons (13-15) were added. These lessons can be either optional or serve as an introduction to statistical inference with dependent observations. Several points of this text need to be elaborated, (1) The pedagogy is somewhat obvious. Since this text is designed for a one semester course, each lesson can be covered in one week or so. Having in mind a mixed audience of students from different departments (Math­ ematics, Statistics, Economics, Engineering, etc.) we have presented the material in each lesson in the most simple way, with emphasis on moti­ vation of concepts, aspects of applications and computational procedures. Basically, we try to explain to beginners questions such as "What is the topic in this lesson?" "Why this topic?", "How to study this topic math­ ematically?". The exercises at the end of each lesson will deepen the stu­ dents' understanding of the material, and test their ability to carry out basic computations. Exercises with an asterisk are optional (difficult) and might not be suitable for homework, but should provide food for thought.

Keywords

Brownian motion Markov Chain Markov Chains Martingale Poisson process Random Walk Stochastic Processes Stochastic model Stochastic models Symbol diffusion process point process queueing theory renewal theory statistics

Authors and affiliations

  • Denis Bosq
    • 1
  • Hung T. Nguyen
    • 2
  1. 1.Institut de StatistiqueUniversité Pierre et Marie CurieParisFrance
  2. 2.Department of Mathematical SciencesNew Mexico State UniversityLas CrucesUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-015-8769-3
  • Copyright Information Springer Science+Business Media B.V. 1996
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-4713-7
  • Online ISBN 978-94-015-8769-3
  • Buy this book on publisher's site
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