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Produktbild: Bayesian Theory and Applications

Bayesian Theory and Applications

123,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

26.02.2015

Abbildungen

121 b/w line drawings & 21 b/w halftones

Herausgeber

Damien Paul + weitere

Verlag

Oxford University Press

Seitenzahl

718

Maße (L/B/H)

23,4/15,6/3,8 cm

Gewicht

1071 g

Sprache

Englisch

ISBN

978-0-19-873907-4

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

26.02.2015

Abbildungen

121 b/w line drawings & 21 b/w halftones

Herausgeber

Verlag

Oxford University Press

Seitenzahl

718

Maße (L/B/H)

23,4/15,6/3,8 cm

Gewicht

1071 g

Sprache

Englisch

ISBN

978-0-19-873907-4

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Bayesian Theory and Applications


    • Introduction


    • I EXCHANGEABILITY


    • 1: Michael Goldstein: Observables and Models: exchangeability and the inductive argument


    • 2: A. Philip Dawid: Exchangeability and its Ramifications


    • II HIERARCHICAL MODELS


    • 3: Alan E. Gelfand and Souparno Ghosh: Hierarchical Modeling


    • 4: Sounak Chakraborty, Bani K Mallick and Malay Ghosh: Bayesian Hierarchical Kernel Machines for Nonlinear Regression and Classification


    • 5: Athanasios Kottas and Kassandra Fronczyk: Flexible Bayesian modelling for clustered categorical responses in developmental toxicology


    • III MARKOV CHAIN MONTE CARLO


    • 6: Siddartha Chib: Markov chain Monte Carlo Methods


    • 7: Jim E. Griffin and David A. Stephens: Advances in Markov chain Monte Carlo


    • IV DYNAMIC MODELS


    • 8: Mike West: Bayesian Dynamic Modelling


    • 9: Dani Gamerman and Esther Salazar: Hierarchical modeling in time series: the factor analytic approach


    • 10: Gabriel Huerta and Glenn A. Stark: Dynamic and spatial modeling of block maxima extremes


    • V SEQUENTIAL MONTE CARLO


    • 11: Hedibert F. Lopes and Carlos M. Carvalho: Online Bayesian learning in dynamic models: An illustrative introduction to particle methods


    • 12: Ana Paula Sales, Christopher Challis, Ryan Prenger, and Daniel Merl: Semi-supervised Classification of Texts Using Particle Learning for Probabilistic Automata


    • VI NONPARAMETRICS


    • 13: Stephen G Walker: Bayesian Nonparametrics


    • 14: RamsÃ(c)s H. Mena: Geometric Weight Priors and their Applications


    • 15: Stephen G. Walker and George Karabatsos: Revisiting Bayesian Curve Fitting Using Multivariate Normal Mixtures


    • VII SPLINE MODELS AND COPULAS


    • 16: Sally Wood: Applications of Bayesian Smoothing Splines


    • 17: Michael Stanley Smith: Bayesian Approaches to Copula Modelling


    • VIII MODEL ELABORATION AND PRIOR DISTRIBUTIONS


    • 18: M.J. Bayarri and J.O. Berger: Hypothesis Testing and Model Uncertainty


    • 19: E. GutiÃ(c)rrez-Peña and M. Mendoza: Proper and non-informative conjugate priors for exponential family models


    • 20: David Draper: Bayesian Model Specification: Heuristics and Examples


    • 21: Zesong Liu, Jesse Windle, and James G. Scott: Case studies in Bayesian screening for time-varying model structure: The partition problem


    • IX REGRESSIONS AND MODEL AVERAGING


    • 22: Hugh A. Chipman, Edward I. George and Robert E. McCulloch: Bayesian Regression Structure Discovery


    • 23: Robert B. Gramacy: Gibbs sampling for ordinary, robust and logistic regression with Laplace priors


    • 24: Merlise Clyde and Edwin S. Iversen: Bayesian Model Averaging in the M-Open Framework


    • X FINANCE AND ACTUARIAL SCIENCE


    • 25: Eric Jacquier and Nicholas G Polson: Asset Allocation in Finance: A Bayesian Perspective


    • 26: Arthur Korteweg: Markov Chain Monte Carlo Methods in Corporate Finance


    • 27: Udi Makov: Actuarial Credibity Theory and Bayesian Statistics - The Story of a Special Evolution


    • XI MEDICINE AND BIOSTATISTICS


    • 28: Peter Mÿller: Bayesian Models in Biostatistics and Medicine


    • 29: Purushottam W. Laud, Siva Sivaganesan and Peter Mÿller: Subgroup Analysis


    • 30: Timothy E. Hanson and Alejandro Jara: Surviving Fully Bayesian Nonparametric Regression Models


    • XII INVERSE PROBLEMS AND APPLICATIONS


    • 31: Colin Fox, Heikki Haario and J. AndrÃ(c)s Christen: Inverse Problems


    • 32: Jari Kaipio and Ville Kolehmainen: Approximate marginalization over modeling errors and uncertainties in inverse problems


    • 33: C. Nakhleh, D. Higdon, C. K. Allen and R. Ryne: Bayesian reconstruction of particle beam phase space