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Advances in Modeling and Simulation Festschrift for Pierre L'Ecuyer
Title
Advances in Modeling and Simulation [electronic resource] : Festschrift for Pierre L'Ecuyer / edited by Zdravko Botev, Alexander Keller, Christiane Lemieux, Bruno Tuffin.
ISBN
9783031101939
Edition
1st ed. 2022.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2022.
Physical Description
1 online resource (XVI, 420 p.) 91 illus., 72 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ENIN.
Other formats
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Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
December 01, 2022
Contents
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.
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