Handbook of Approximate Bayesian Computation: Likelihood-Free Methods for Comple

Description: Handbook of Approximate Bayesian Computation by Scott A. Sisson, Yanan Fan, Mark Beaumont The Handbook of ABC provides illuminating insight into the world of Bayesian modelling for intractable models for both experts and newcomers alike. It is an essential reference book for anyone interested in learning about and implementing ABC techniques to analyse complex models in the modern world. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of ABC methods. These simple, but powerful statistical techniques, take Bayesian statistics beyond the need to specify overly simplified models, to the setting where the model is defined only as a process that generates data. This process can be arbitrarily complex, to the point where standard Bayesian techniques based on working with tractable likelihood functions would not be viable. ABC methods finesse the problem of model complexity within the Bayesian framework by exploiting modern computational power, thereby permitting approximate Bayesian analyses of models that would otherwise be impossible to implement.The Handbook of ABC provides illuminating insight into the world of Bayesian modelling for intractable models for both experts and newcomers alike. It is an essential reference book for anyone interested in learning about and implementing ABC techniques to analyse complex models in the modern world. Author Biography Scott Sission is Professor, ARC Future Fellow and Head of Statistics in the School of Mathematics and Statistics at UNSW.Yanan Fan is a Senior Lecturer at the School of Mathematics and Statistics at UNSW.Mark Beaumont is Professor of Statistics at the University of Bristol. Table of Contents IntroductionOverview of approximate Bayesian computation: S. A. Sisson, Y. Fan and M. A. BeaumontOn the history of ABC: S.Tavar–eRegression approaches: M. G. B. BlumMonte Carlo samplers for ABC: Y. Fan and S. A. SissonSummary statistics: D. PrangleLikelihood-free model choose: J.-M. Marin, P. Pudlo, A. Estoup and C. RobertABC and indirect inference: C. C. DrovandiHigh-dimensional ABC: D. Nott, V. Ong, Y. Fan and S. A. Sisson Theoretical and methodological aspects of MCMC computations with noisy likelihoods: C. Andrieu, A.Lee and M. ViolaInformed Choices: How to calibrate ABC with hypothesis testing: O. Ratmann, A. Camacho, S. Hu and C. ColjinApproximating the likelihood in approximate Bayesian computation: C. C. Drovandi, C. Grazian, K. Mengersen and C. RobertSoftware: D.WegmannDivide and conquer in ABC: Expectation-Propagation algorithms for likelihood-free inference: S. Barthelm–e, N. Chopin and V. CottetSMC-ABC methods for estimation of stochastic simulation models of the limit order book: G.W. Peters, E. Panayi and F. SeptierInferences on the acquisition of multidrug resistance in Mycobacterium tuberculosis using molecular epidemiological data: G. S. Rodrigues, S. A. Sisson, M. M. TanakaABC in Systems Biology: J. Liepe and M. P. H. StumpfApplication of approximate Bayesian computation to make inference about the genetic history of Pygmy hunter-gatherers populations from Western Central Africa: A. Estoup et alABC for climate: dealing with expensive simulators: P. B. Holden, N. R. Edwards, J. Hensman and R. D. WilkinsonABC in ecological modelling: M. Fasiolo and S. N. WoodABC in Nuclear Imaging: Y. Fan, S. R. Meikle, G. Angelis and A. Sitek Review "The Handbook of Approximate Bayesian Computation presents basic approaches as well as extension and mathematical details about ABC approaches. Advantages (simplicity, wide applicability) as well as challenges (computational burden, various assumptions/choice of tuning parameters) of ABC are discussed in theory and application ... the Handbook of Approximate Bayesian Computation is an excellent book and an indispensable choice for all (beginners and advanced users) who are interested in obtaining a deeper understanding of ABC approaches in application as well as statistical theory."-Heiko Götte, Merck Healthcare KGaA, Darmstadt, Germany Review Quote "The Handbook of Approximate Bayesian Computation presents basic approaches as well as extension and mathematical details about ABC approaches. Advantages (simplicity, wide applicability) as well as challenges (computational burden, various assumptions/choice of tuning parameters) of ABC are discussed in theory and application ... the Handbook of Approximate Bayesian Computation is an excellent book and an indispensable choice for all (beginners and advanced users) who are interested in obtaining a deeper understanding of ABC approaches in application as well as statistical theory." - Heiko G Details ISBN1439881502 Author Mark Beaumont ISBN-10 1439881502 ISBN-13 9781439881507 Format Hardcover Birth 1983 DEWEY 519.542 Edited by Scott A. Sisson Series Chapman & Hall/CRC Handbooks of Modern Statistical Methods Affiliation University of Bristol, UK Pages 662 Publisher Taylor & Francis Inc Year 2018 Place of Publication Washington Country of Publication United States Short Title Approximate Bayesian Computation Language English Subtitle Likelihood-Free Methods for Complex Models Publication Date 2018-08-10 AU Release Date 2018-08-10 NZ Release Date 2018-08-10 US Release Date 2018-08-10 UK Release Date 2018-08-10 Illustrations 34 Tables, black and white; 114 Illustrations, black and white Alternative 9780367733728 Audience General Imprint Chapman & Hall/CRC We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:119103718;

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