Advertisement

Monte Carlo and Quasi-Monte Carlo Methods

MCQMC 2016, Stanford, CA, August 14-19

  • Art B. Owen
  • Peter W. Glynn
Conference proceedings MCQMC 2016

Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 241)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Tutorials

  3. Invited Talks

  4. Regular Talks

    1. Front Matter
      Pages 167-167
    2. Christoph Aistleitner, Dmitriy Bilyk, Aleksandar Nikolov
      Pages 169-180
    3. Ken Dahm, Alexander Keller
      Pages 181-195
    4. J. Feng, M. Huber, Y. Ruan
      Pages 235-248
    5. Michael B. Giles, Frances Y. Kuo, Ian H. Sloan
      Pages 265-281
    6. Masatake Hirao
      Pages 331-343
    7. Ralph Kritzinger, Helene Laimer, Mario Neumüller
      Pages 377-394
    8. David Mandel, Giray Ökten
      Pages 395-408
    9. Hisanari Otsu, Shinichi Kinuwaki, Toshiya Hachisuka
      Pages 409-427
    10. Pieterjan Robbe, Dirk Nuyens, Stefan Vandewalle
      Pages 429-445
    11. Shuang Zhao, Rong Kong, Jerome Spanier
      Pages 447-463
    12. Zeyu Zheng, Jose Blanchet, Peter W. Glynn
      Pages 465-479

About these proceedings

Introduction

This book presents the refereed proceedings of the Twelfth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at Stanford University (California) in August 2016.  These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. 

The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising in particular, in finance, statistics, computer graphics and the solution of PDEs.

Keywords

Monte Carlo Quasi-Monte Carlo Markov Chain Monte Carlo Simulation Stochastic Computation Bayesian Computation Graphical Rendering Lattice Rules Probabilistic Numerics Importance Sampling Computational Complexity Cubature Discrepancy Multilevel Monte Carlo Quadrature Sequential Monte Carlo

Editors and affiliations

  • Art B. Owen
    • 1
  • Peter W. Glynn
    • 2
  1. 1.Department of StatisticsStanford UniversityStanfordUSA
  2. 2.Department of Management Science and EngineeringStanford UniversityStanfordUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-91436-7
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-91435-0
  • Online ISBN 978-3-319-91436-7
  • Series Print ISSN 2194-1009
  • Series Online ISSN 2194-1017
  • Buy this book on publisher's site