Luca Martino, David Luengo, Joaquín Míguez

Independent Random Sampling Methods (eBook, PDF)

• Format: PDF

Produktbeschreibung

Presents an up-to-date survey of random sampling methods

Offers useful methods for practitioners together with detailed analyses for researchers in computational statistics

Covers random sampling from multivariate distributions

Features a wealth of examples with accompanying computer code

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 280
• Erscheinungstermin: 31. März 2018
• Englisch
• ISBN-13: 9783319726342
• Artikelnr.: 52943456

Autorenporträt

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.

Inhaltsangabe

Introduction.- Direct methods.- Accept-Reject methods.- Adaptive rejection sampling methods.- Ratio of Uniforms.- Independent sampling for multivariate densities.- Asymptotically independent samplers.- Summary and outlook.- A. Acronyms and abbrevations.- B. Notation.- C. Jones' RoU generalization.- D. Polar transformation.

Rezensionen

"The book contains more than 300 references and has more than 50 coloured figures for better understanding. The book can be recommended to all readers, who are interested in this field, e.g. 'engineers working in signal theory or statisticians interested in computational methods or scientists working in the fields of biology, quantitative finance or physics, where complex models that demand Monte Carlo computations are needed'." (Ludwig Paditz, zbMATH 1414.62007, 2019)

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