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The effects of common random numbers on stochastic kriging metamodels
Xi Chen, Bruce E. Ankenman, Barry L. Nelson
Article No.: 7
Ankenman et al. introduced stochastic kriging as a metamodeling tool for representing stochastic simulation response surfaces, and employed a very simple example to suggest that the use of Common Random Numbers (CRN) degrades the capability of...
On importance sampling with mixtures for random walks with heavy tails
Henrik Hult, Jens Svensson
Article No.: 8
State-dependent importance sampling algorithms based on mixtures are considered. The algorithms are designed to compute tail probabilities of a heavy-tailed random walk. The increments of the random walk are assumed to have a regularly varying...
Evolutionary optimization of low-discrepancy sequences
François-Michel De Rainville, Christian Gagné, Olivier Teytaud, Denis Laurendeau
Article No.: 9
Low-discrepancy sequences provide a way to generate quasi-random numbers of high dimensionality with a very high level of uniformity. The nearly orthogonal Latin hypercube and the generalized Halton sequence are two popular methods when it comes...
Confidence intervals for quantiles when applying variance-reduction techniques
Fang Chu, Marvin K. Nakayama
Article No.: 10
Quantiles, which are also known as values-at-risk in finance, frequently arise in practice as measures of risk. This article develops asymptotically valid confidence intervals for quantiles estimated via simulation using variance-reduction...
Fast synthesis of persistent fractional Brownian motion
Pedro R. M. Inácio, Mário M. Freire, Manuela Pereira, Paulo P. Monteiro
Article No.: 11
Due to the relevance of self-similarity analysis in several research areas, there is an increased interest in methods to generate realizations of self-similar processes, namely in the ones capable of simulating long-range dependence. This article...
Given a black box that generates independent Bernoulli samples with an unknown bias p, we consider the problem of simulating a Bernoulli random variable with bias f(p) (where f is a given function) using a finite (computable...