Applied Probability and Stochastic Processes

  • Editors
  • J. G. Shanthikumar
  • Ushio Sumita

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 19)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. R. Syski, N. Liu
    Pages 1-15
  3. Lajos Takács
    Pages 45-62
  4. I. N. Kovalenko, M. N. Savchuk
    Pages 73-82
  5. Erol Pekoz, Sheldon M. Ross
    Pages 83-94
  6. Moshe Shaked, Tityik Wong
    Pages 115-127
  7. David D. Yao, Shaohui Zheng
    Pages 129-147
  8. Teunis J. Ott, J. George Shanthikumar
    Pages 173-189
  9. Shaler Stidham Jr., Richard R. Weber
    Pages 191-202
  10. H. M. Liang, V. G. Kulkarni
    Pages 203-218
  11. Donald P. Gaver, Patricia A. Jacobs
    Pages 219-229
  12. Peter W. Glynn, Ward Whitt
    Pages 231-246
  13. Ushio Sumita, Masaaki Sibuya, Norihiko Miyawaki
    Pages 247-262

About this book

Introduction

Applied Probability and Stochastic Processes is an edited work written in honor of Julien Keilson. This volume has attracted a host of scholars in applied probability, who have made major contributions to the field, and have written survey and state-of-the-art papers on a variety of applied probability topics, including, but not limited to: perturbation method, time reversible Markov chains, Poisson processes, Brownian techniques, Bayesian probability, optimal quality control, Markov decision processes, random matrices, queueing theory and a variety of applications of stochastic processes.
The book has a mixture of theoretical, algorithmic, and application chapters providing examples of the cutting-edge work that Professor Keilson has done or influenced over the course of his highly-productive and energetic career in applied probability and stochastic processes. The book will be of interest to academic researchers, students, and industrial practitioners who seek to use the mathematics of applied probability in solving problems in modern society.

Keywords

Analysis Brownian bridge Markov Markov Chain Markov Chains Markov decision process Poisson process Random variable Stochastic Processes Transformation algorithm local time queueing theory stochastic process

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-5191-1
  • Copyright Information Kluwer Academic Publishers 1999
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7364-3
  • Online ISBN 978-1-4615-5191-1
  • Series Print ISSN 0884-8289
  • About this book