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Monte Carlo and Quasi-Monte Carlo Methods 1996

Proceedings of a conference at the University of Salzburg, Austria, July 9–12, 1996

  • Harald Niederreiter
  • Peter Hellekalek
  • Gerhard Larcher
  • Peter Zinterhof

Part of the Lecture Notes in Statistics book series (LNS, volume 127)

Table of contents

  1. Front Matter
    Pages N2-xii
  2. Peter A. Acworth, Mark Broadie, Paul Glasserman
    Pages 1-18
  3. Jürgen Eichenauer-Herrmann, Eva Herrmann, Stefan Wegenkittl
    Pages 66-97
  4. Paul Glasserman, Philip Heidelberger, Perwez Shahabuddin, Tim Zajic
    Pages 98-108
  5. Gerhard Larcher
    Pages 109-123
  6. Pierre L’Ecuyer
    Pages 124-138
  7. Harald Niederreiter, Chaoping Xing
    Pages 139-160
  8. I. Dimov, U. Jaekel, H. Vereecken, D. Wendt
    Pages 189-204
  9. I. T. Dimov, A. N. Karaivanova, P. I. Yordanova
    Pages 205-220
  10. Yves Edel, Jürgen Bierbrauer
    Pages 221-231
  11. Peter Hellekalek
    Pages 251-265
  12. Jiri Hoogland, Fred James, Ronald Kleiss
    Pages 266-276
  13. Alexander Keller
    Pages 277-291
  14. Gerhard Larcher, Gottlieb Pirsic, Reinhard Wolf Salzburg
    Pages 321-329
  15. Hannes Leeb
    Pages 330-339
  16. William J. Morokoff, Russel E. Caflisch
    Pages 340-352
  17. Jerome Spanier, Liming Li
    Pages 398-414
  18. Peter Winker, Kai-Tai Fang
    Pages 436-448
  19. Back Matter
    Pages 449-450

About these proceedings

Introduction

Monte Carlo methods are numerical methods based on random sampling and quasi-Monte Carlo methods are their deterministic versions. This volume contains the refereed proceedings of the Second International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at the University of Salzburg (Austria) from July 9--12, 1996. The conference was a forum for recent progress in the theory and the applications of these methods. The topics covered in this volume range from theoretical issues in Monte Carlo and simulation methods, low-discrepancy point sets and sequences, lattice rules, and pseudorandom number generation to applications such as numerical integration, numerical linear algebra, integral equations, binary search, global optimization, computational physics, mathematical finance, and computer graphics. These proceedings will be of interest to graduate students and researchers in Monte Carlo and quasi-Monte Carlo methods, to numerical analysts, and to practitioners of simulation methods.

Keywords

Estimator Random variable algorithms correlation optimization

Editors and affiliations

  • Harald Niederreiter
    • 1
  • Peter Hellekalek
    • 2
  • Gerhard Larcher
    • 2
  • Peter Zinterhof
    • 2
  1. 1.Institute of Information ProcessingAustrian Academy of SciencesViennaAustria
  2. 2.Department of MathematicsUniversity of SalzburgSalzburgAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-1690-2
  • Copyright Information Springer-Verlag New York, Inc. 1998
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-98335-6
  • Online ISBN 978-1-4612-1690-2
  • Series Print ISSN 0930-0325
  • Series Online ISSN 2197-7186
  • Buy this book on publisher's site