Advances in Modeling and Simulation: Festschrift for Pierre L'Ecuyer

ISBN-13: 9783031101922 / Angielski / Twarda / 2022 / 420 str.

Zdravko Botev; Alexander Keller; Christiane LeMieux

Opis

This book celebrates the career of Pierre L’Ecuyer on the occasion of his 70th birthday. Pierre has made significant contributions to the fields of simulation, modeling, and operations research over the last 40 years. This book contains 20 chapters written by collaborators and experts in the field who, by sharing their latest results, want to recognize the lasting impact of Pierre’s work in their research area. The breadth of the topics covered reflects the remarkable versatility of Pierre's contributions, from deep theoretical results to practical and industry-ready applications. The Festschrift features article from the domains of Monte Carlo and quasi-Monte Carlo methods, Markov chains, sampling and low discrepancy sequences, simulation, rare events, graphics, finance, machine learning, stochastic processes, and tractability.

Spis treści

Part I Pierre L’Ecuyer: Biography, Part II Invited Contributions: Monte Carlo Methods for Pricing American Options.- Remarks on Levy Process Simulation.- Exact Sampling for the Maximum of Infinite Memory Gaussian Processes.- Truncated Multivariate Student Computations via Exponential Tilting.- Quasi-Monte Carlo Methods in Portfolio Selection with Many Constraints.- Geometric-Moment Contraction of G/G/1 Waiting Times.- Tractability of Approximation in the Weighted Korobov Space in the Worst-Case Setting.- Rare-Event Simulation via Neural Networks.- Preintegration is Not Smoothing when Monotonicity Fails.- Combined Derivative Estimators.- A Central Limit Theorem For Empirical Quantiles in the Markov Chain Setting.- Simulation of Markov Chains with Continuous State Space by Using Simple Stratified and Sudoku Latin Square Sampling.- Quasi-Random Sampling with Black Box or Acceptance-Rejection Inputs.- A Generalized Transformed Density Rejection Algorithm.- Fast Automatic Bayesian Cubature Using Sobol’ Sampling.- Rendering along the Hilbert Curve.- Array-RQMC to Speed Up the Simulation for Estimating the Hitting-Time Distribution to a Rare Set of a Regenerative System.- Foundations of Ranking & Selection for Simulation Optimization.- Where are the Logs?.- Network Reliability, Performability Metrics, Rare Events and Standard Monte Carlo.

O autorze

Zdravko Botev is a Statistics Lecturer at UNSW Sydney. He is the inventor of the widely used kernel density estimation via diffusion,  as well as the generalized splitting method for rare-event simulation and optimization. His research has been recognized with the Christopher Heyde Medal of the Australian Academy of Sciences, as well as the Gavin Brown Prize of the Australian Mathematical Society. 

Alexander Keller is a Director of Research at NVIDIA working on the foundations of graphics, communications, and machine learning. Before, he had been the Chief Scientist of mental images. Prior to industry, he worked as a full professor for computer graphics and scientific computing at Ulm University

Christiane Lemieux is a Professor in the Department of Statistics and Actuarial Science in the Faculty of Mathematics at the University of Waterloo in Canada. Her research interests are centered on quasi-Monte Carlo methods and their applications in practice. Her most recent work includes studying the negative dependence properties of scrambled constructions and devising sampling algorithms based on low-discrepancy sequences for multivariate distributions, including copula models.

Bruno Tuffin is a Research Director at Inria Rennes, France. He is leading the Ermine research team focusing on an efficient management of communication networks operations. His own research interests include developing Monte Carlo and quasi-Monte Carlo simulation techniques  for the performance evaluation of telecommunication systems and telecommunication-related economical models. He has written or co-written four books on those topics.