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An Introduction to Probabilistic Modeling

  • Pierre Brémaud

Part of the Undergraduate Texts in Mathematics book series (UTM)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Pierre Brémaud
    Pages 1-45
  3. Pierre Brémaud
    Pages 46-84
  4. Pierre Brémaud
    Pages 85-127
  5. Pierre Brémaud
    Pages 128-162
  6. Pierre Brémaud
    Pages 163-192
  7. Back Matter
    Pages 193-208

About this book

Introduction

Introduction to the basic concepts of probability theory: independence, expectation, convergence in law and almost-sure convergence. Short expositions of more advanced topics such as Markov Chains, Stochastic Processes, Bayesian Decision Theory and Information Theory.

Keywords

Branching process Conditional probability Markov chain Poisson process Probability space Probability theory Random variable Stochastic processes Variance coding stochastic process

Authors and affiliations

  • Pierre Brémaud
    • 1
  1. 1.Laboratoire des Signaux et SystèmesCNRSGif-sur-YvetteFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-1046-7
  • Copyright Information Springer-Verlag New York Inc. 1988
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-96460-7
  • Online ISBN 978-1-4612-1046-7
  • Series Print ISSN 0172-6056
  • Buy this book on publisher's site