Synopsis
Presents an up-to-date survey of random sampling methodsOffers useful methods for practitioners together with detailed analyses for researchers in computational statisticsCovers random sampling from multivariate distributionsFeatures a wealth of examples with accompanying computer code
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Luca Martino is currently a research fellow at the University of Valencia, Spain, after having held positions at the Carlos III University of Madrid, Spain, the University of Helsinki, Finland and the University of São Paulo, Brazil. His research interests are in the fields of statistical signal processing and computational statistics, especially in connection with Bayesian analysis and Monte Carlo approximation methods.
David Luengo is an Associate Professor at the Technical University of Madrid, Spain. His research interests are in the broad fields of statistical signal processing and machine learning, especially Bayesian learning and inference, Gaussian processes, Monte Carlo algorithms, sparse signal processing and Bayesian non-parametrics. Dr. Luengo has co-authored over 70 research papers, which were published in international journals and conference volumes.
Joaquín Míguez is an Associate Professor at the Carlos III University of Madrid, Spain. His interests are in the fields of applied probability, computational statistics, dynamical systems and the theory and applications of the Monte Carlo methods. Having published extensively and lectured internationally on his research, he was a co-recipient of the IEEE Signal Processing Magazine Best Paper Award in 2007.
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Independent Random Sampling Methods.
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Cham, Springer., 2018
ISBN 10 : 3319726331
ISBN 13 : 9783319726335
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Independent Random Sampling Methods (Statistics and Computing)
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Springer, 2018
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Hardcover. Etat : Fine. 1st Edition. Hardcover, xii + 280 pages, NOT ex-library. Book looks unread, clean and bright throughout with unmarked text, free of inscriptions and stamps, firmly bound. Issued without a dust jacket. -- Contents: 1 Introduction: -- Monte Carlo Method: A Brief History; Need for Monte Carlo; Random Number Generation; Pseudo-Random Number Generators; Random Sampling Methods; Goal and Organization of This Book; References; 2 Direct Methods: -- Introduction; Notation; Transformations of Random Variables; Universal Direct Methods; Tailored Techniques; Examples; Summary; 3 Accept-Reject Methods: -- Introduction; Rejection Sampling; Computational Cost; Band Rejection Method; Acceptance-Complement Method; RS with Stepwise Proposals; Transformed Rejection Method; Examples; Monte Carlo Estimation via RS; Summary; 4 Adaptive Rejection Sampling Methods: -- Introduction; Generic Structure of an Adaptive Rejection Sampler; Constructions of the Proposal Densities; Performance and Computational Cost of the ARS Schemes; Variants of the Adaptive Structure in the ARS Scheme; Combining ARS and MCMC; Summary; 5 Ratio of Uniforms: -- Introduction; Standard Ratio of Uniforms Method; Envelope Polygons and Adaptive RoU; Generalized Ratio of Uniforms Method; Properties of Generalized RoU Samplers; Connections Between GRoU and Other Classical Techniques; How Does GRoU Work for Generic Pdfs?; Rectangular Region Ag; Relaxing Assumptions: GRoU with Decreasing g(u); Another View of GRoU; Summary; 6 Independent Sampling for Multivariate Densities: -- Introduction; Notation; Generic Procedures; Elliptically Contoured Distributions; Vertical Density Representation; Uniform Distributions in Dimension n; Transformations of a Random Variable; Sampling Techniques for Specific Distributions; Generation of Stochastic Processes; Summary; 7 Asymptotically Independent Samplers: -- Introduction; Metropolis-Hastings (MH) Methods; Independent Generalized MH Methods with Multiple Candidates; Independent Doubly Adaptive Rejection Metropolis Sampling Adaptive Rejection Sampling (Ars) Adaptive Rejection Metropolis Sampling; Summary; 8 Summary and Outlook: A. Acronyms and Abbreviations B. Notation C Jones' RoU Generalization D Polar Transformation -- 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 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, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code. The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the links and interplay between ostensibly diverse techniques. N° de réf. du vendeur 005875
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Independent Random Sampling Methods
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ISBN 13 : 9783319726335
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Independent Random Sampling Methods
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Independent Random Sampling Methods
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Springer International Publishing Apr 2018, 2018
ISBN 10 : 3319726331
ISBN 13 : 9783319726335
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 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, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code.The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the links and interplay between ostensibly diverse techniques. 292 pp. Englisch. N° de réf. du vendeur 9783319726335
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