Titlebook: Independent Random Sampling Methods; Luca Martino,David Luengo,Joaquín Míguez Book 2018 Springer International Publishing AG, part of Spr

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Adaptive Rejection Sampling Methods,ctical applicability of this methodology. As a consequence, ARS schemes are often tailored to specific classes of target distributions. Indeed, the construction of the proposal is particularly hard in multidimensional spaces. Hence, ARS algorithms are usually designed only for drawing from univariat

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Asymptotically Independent Samplers,he second family rely on an adaptive, non-parametric approximation of the target density, which is improved as new samples are generated. We describe the general methodology for the two families, and provide some specific algorithms as examples.

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Book 2018which can be used to generate samples from arbitrary probability distributions, and tailored techniques, designed to efficiently address common real-world practical problems, are introduced and discussed in detail. In turn, the monograph presents fundamental results and methodologies in the field, e

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Introduction,i-random), a brief description of some pseudo-random number generators and an overview of the different classes of random sampling methods available in the literature: direct, accept/reject, MCMC, importance sampling, and hybrid. Finally, the chapter concludes with an exposition of the motivation, goals, and organization of the book.

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1431-8784 hers in computational statistics.Covers random sampling from.This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailor