Independent Random Sampling Methods

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

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

Autorentext

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.

Inhalt
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.