Bayesian Model Comparison (BOK)

Dale Poirier

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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.

Produktfakta

Språk Engelsk Engelsk Innbinding Innbundet
Utgitt 2014 Forfatter Dale Poirier
Forlag
Emerald Group Publishing Ltd
ISBN 9781784411855
Antall sider 390 Dimensjoner 15,8cm x 23,1cm x 3,3cm
Vekt 672 gram Leverandør Bertram Trading Ltd
Andre medvirkende Dale J. Poirier, Ivan Jeliazkov

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