Proceedings of a Conference held at the National University of Singapore, Republic of Singapore, November 25¿28, 2002
Buch, Englisch, 460 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 1490 g
ISBN: 978-3-540-20466-4
Verlag: Springer Berlin Heidelberg
This volume contains the refereed proceedings of the Fifth International Con ference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Com puting (MCQMC 2002) which was held at the National University of Sin gapore from 25-28 November 2002. The programme of this conference was arranged by a committee consisting of Kai-Tai Fang (Hong Kong Baptist University), Paul Glasserman (Columbia University), Stefan Heinrich (Uni versitat Kaiserslautern), Fred J. Hickernell (Hong Kong Baptist University), Pierre L'Ecuyer (Universite de Montreal), Harald Niederreiter (National Uni versity of Singapore, chair), Erich Novak (Universitat Jena), Art B. Owen (Stanford University), Ian H. Sloan (University of New South Wales), Jerome Spanier (Claremont Graduate University), Denis Talay (INRIA Sophia An tipolis), Simon Tavare (University of Southern California), Jian-Sheng Wang (National University of Singapore) and Henryk Wozniakowski (Columbia Uni versity and University of Warsaw). MCQMC 2002 continued the tradition of biennial MCQMC conferences which was begun at the University of Nevada in Las Vegas, Nevada, USA, in June 1994 and followed by conferences at the University of Salzburg, Austria, in July 1996, the Claremont Colleges in Claremont, California, USA, in June 1998 and Hong Kong Baptist University in Hong Kong, China, in November 2000. The proceedings of these previous conferences were all published by Springer-Verlag, under the titles Monte Carlo and Quasi-Monte Carlo Meth ods in Scientific Computing (H. Niederreiter and P. J. -S. Shiue, eds. ), Monte Carlo and Quasi-Monte Carlo Methods 1996 (H. Niederreiter, P.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
Weitere Infos & Material
Invited Papers.- Finance: A Fertile Field for Applications of MC and QMC.- How Many Random Bits Do We Need for Monte Carlo Integration?.- On Tractability of Weighted Integration for Certain Banach Spaces of Functions.- Polynomial Integration Lattices.- Approximate Bayesian Computation and MCMC.- New Challenges for the Simulation of Stochastic Processes.- Stochastic Models and Monte Carlo Algorithms for Boltzmann Type Equations.- Digital Nets, Duality, and Algebraic Curves.- Contributed Papers.- Generalized Mersenne Prime Number and Its Application to Random Number Generation.- Constructing Good Lattice Rules with Millions of Points.- Lattice Structure of Nonlinear Pseudorandom Number Generators in Parts of the Period.- Simulation for American Options: Regression Now or Regression Later?.- Perturbation Monte Carlo Methods for the Solution of Inverse Problems.- Quantum Boolean Summation with Repetitions in the Worst-Average Setting.- The Strong Tractability of Multivariate Integration Using Lattice Rules.- Minimizing Effective Dimension Using Linear Transformation.- Component by Component Construction of Rank-1 Lattice Rules Having O(n-1(ln(n))d) Star Discrepancy.- Stratification by Rank-1 Lattices.- Walsh Series Analysis of the Star Discrepancy of Digital Nets and Sequences.- Quasi-Monte Carlo Methods for Estimating Transient Measures of Discrete Time Markov Chains.- Quasi-Monte Carlo Methods for Elliptic BVPs.- Stable Connectivity of Networks and Its Monte Carlo Estimation.- Random Number Generators Based on Linear Recurrences in
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$$.- Using Quasi-Monte Carlo Scenarios in Risk Management.- Adaptive Quasi-Monte Carlo Integration Based on MISER and VEGAS.- When Does Monte Carlo Depend Polynomially on the Number of Variables?.- A New Adaptive Method for Geometric Convergence.- Polynomial Arithmetic Analogue of Hickernell Sequences.
