Approximation Methods in Probability Theory

  • Vydas Čekanavičius

Part of the Universitext book series (UTX)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Vydas Čekanavičius
    Pages 1-20
  3. Vydas Čekanavičius
    Pages 21-49
  4. Vydas Čekanavičius
    Pages 51-68
  5. Vydas Čekanavičius
    Pages 69-76
  6. Vydas Čekanavičius
    Pages 77-92
  7. Vydas Čekanavičius
    Pages 93-100
  8. Vydas Čekanavičius
    Pages 101-106
  9. Vydas Čekanavičius
    Pages 107-120
  10. Vydas Čekanavičius
    Pages 121-139
  11. Vydas Čekanavičius
    Pages 141-152
  12. Vydas Čekanavičius
    Pages 153-177
  13. Vydas Čekanavičius
    Pages 179-206
  14. Vydas Čekanavičius
    Pages 207-221
  15. Vydas Čekanavičius
    Pages 223-240
  16. Back Matter
    Pages 241-274

About this book


This book presents a wide range of well-known and less common methods used for estimating the accuracy of probabilistic approximations, including the Esseen type inversion formulas, the Stein method as well as the methods of convolutions and triangle function. Emphasising the correct usage of the methods presented, each step required for the proofs is examined in detail. As a result, this textbook provides valuable tools for proving approximation theorems.

While Approximation Methods in Probability Theory will appeal to everyone interested in limit theorems of probability theory, the book is particularly aimed at graduate students who have completed a standard intermediate course in probability theory. Furthermore, experienced researchers wanting to enlarge their toolkit will also find this book useful.


characteristic function compound distribution inversion formula Kerstan's method m-dependent variables non-uniform estimates smoothing inequalities Stein’s method total variation triangle function

Authors and affiliations

  • Vydas Čekanavičius
    • 1
  1. 1.Vilnius UniversityVilniusLithuania

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-34071-5
  • Online ISBN 978-3-319-34072-2
  • Series Print ISSN 0172-5939
  • Series Online ISSN 2191-6675
  • Buy this book on publisher's site
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