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Item Details
Title: BAYESIAN MODEL COMPARISON
By: Ivan Jeliazkov (Editor), Dale J. Poirier (Editor)
Format: Hardback

List price: £120.99
Our price: £108.89
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ISBN 10: 178441185X
ISBN 13: 9781784411855
Availability: This item will be printed on demand and will usually be dispatched within 10 days.
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Publisher: EMERALD PUBLISHING LIMITED
Pub. date: 21 November, 2014
Series: Advances in Econometrics 34
Pages: 390
Description: This volume of Advances in Econometrics 34 focusses on Bayesian model comparison. It reflects the recent progress in model building and evaluation that has been achieved in the Bayesian paradigm and provides new state-of-the-art techniques, methodology, and findings that should stimulate future research.
Synopsis: The volume contains articles that should appeal to readers with computational, modeling, theoretical, and applied interests. Methodological issues include parallel computation, Hamiltonian Monte Carlo, dynamic model selection, small sample comparison of structural models, Bayesian thresholding methods in hierarchical graphical models, adaptive reversible jump MCMC, LASSO estimators, parameter expansion algorithms, the implementation of parameter and non-parameter-based approaches to variable selection, a survey of key results in objective Bayesian model selection methodology, and a careful look at the modeling of endogeneity in discrete data settings. Important contemporary questions are examined in applications in macroeconomics, finance, banking, labor economics, industrial organization, and transportation, among others, in which model uncertainty is a central consideration.
Publication: UK
Imprint: Emerald Publishing Limited
Returns: Non-returnable
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