Bayesian model comparison /:
This volume of Advances in econometrics is devoted to 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 resea...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Bingley :
Emerald,
2014.
|
| Ausgabe: | 1st ed. |
| Schriftenreihe: | Advances in econometrics ;
v. 34. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | This volume of Advances in econometrics is devoted to 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. 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. |
| Beschreibung: | 1 online resource (xi, 348 pages) |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 1322448264 9781322448268 9781784411848 1784411841 9781784411855 178441185X |
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| contents | Adaptive sequential posterior simulators for massively parallel computing environments -- Model switching and model averaging in time-varying parameter regression models -- Assessing Bayesian model comparison in small samples -- Bayesian selection of systemic risk networks -- Parallel constrained Hamiltonian Monte Carlo for Bekk model comparison -- Factor selection in dynamic hedge fund replication models: a Bayesian approach -- Determining the proper specification for endogenous covariates in discrete data settings -- Variable selection in Bayesian models: using parameter estimation and non paramter estimation methods -- Intrinsic priors for objective Bayesian model selection -- Demand estimation with high-dimensional product characteristics -- Copula analysis of correlated counts. |
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| spelling | Bayesian model comparison / edited by Ivan Jeliazkov, Dale J. Poirier. 1st ed. Bingley : Emerald, 2014. 1 online resource (xi, 348 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Advances in econometrics ; Volume 34 Includes bibliographical references. Adaptive sequential posterior simulators for massively parallel computing environments -- Model switching and model averaging in time-varying parameter regression models -- Assessing Bayesian model comparison in small samples -- Bayesian selection of systemic risk networks -- Parallel constrained Hamiltonian Monte Carlo for Bekk model comparison -- Factor selection in dynamic hedge fund replication models: a Bayesian approach -- Determining the proper specification for endogenous covariates in discrete data settings -- Variable selection in Bayesian models: using parameter estimation and non paramter estimation methods -- Intrinsic priors for objective Bayesian model selection -- Demand estimation with high-dimensional product characteristics -- Copula analysis of correlated counts. Print version record. This volume of Advances in econometrics is devoted to 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. 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. Econometric models. http://id.loc.gov/authorities/subjects/sh85040762 Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Modèles économétriques. Théorie de la décision bayésienne. Econometrics. bicssc BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh Bayesian statistical decision theory fast Econometric models fast Poirier, Dale J., editor. http://id.loc.gov/authorities/names/n80138882 Jeliazkov, Ivan, 1973- editor. https://id.oclc.org/worldcat/entity/E39PCjGRQB3wwrfVj7WbwQ4hjK http://id.loc.gov/authorities/names/n2014019003 has work: Bayesian model comparison (Text) https://id.oclc.org/worldcat/entity/E39PCFDmtgrWCBKcChjPJBcXVC https://id.oclc.org/worldcat/ontology/hasWork 9781784411855 Advances in econometrics ; v. 34. http://id.loc.gov/authorities/names/no98010995 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=924748 Volltext |
| spellingShingle | Bayesian model comparison / Advances in econometrics ; Adaptive sequential posterior simulators for massively parallel computing environments -- Model switching and model averaging in time-varying parameter regression models -- Assessing Bayesian model comparison in small samples -- Bayesian selection of systemic risk networks -- Parallel constrained Hamiltonian Monte Carlo for Bekk model comparison -- Factor selection in dynamic hedge fund replication models: a Bayesian approach -- Determining the proper specification for endogenous covariates in discrete data settings -- Variable selection in Bayesian models: using parameter estimation and non paramter estimation methods -- Intrinsic priors for objective Bayesian model selection -- Demand estimation with high-dimensional product characteristics -- Copula analysis of correlated counts. Econometric models. http://id.loc.gov/authorities/subjects/sh85040762 Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Modèles économétriques. Théorie de la décision bayésienne. Econometrics. bicssc BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh Bayesian statistical decision theory fast Econometric models fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85040762 http://id.loc.gov/authorities/subjects/sh85012506 |
| title | Bayesian model comparison / |
| title_auth | Bayesian model comparison / |
| title_exact_search | Bayesian model comparison / |
| title_full | Bayesian model comparison / edited by Ivan Jeliazkov, Dale J. Poirier. |
| title_fullStr | Bayesian model comparison / edited by Ivan Jeliazkov, Dale J. Poirier. |
| title_full_unstemmed | Bayesian model comparison / edited by Ivan Jeliazkov, Dale J. Poirier. |
| title_short | Bayesian model comparison / |
| title_sort | bayesian model comparison |
| topic | Econometric models. http://id.loc.gov/authorities/subjects/sh85040762 Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Modèles économétriques. Théorie de la décision bayésienne. Econometrics. bicssc BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh Bayesian statistical decision theory fast Econometric models fast |
| topic_facet | Econometric models. Bayesian statistical decision theory. Modèles économétriques. Théorie de la décision bayésienne. Econometrics. BUSINESS & ECONOMICS Economics General. BUSINESS & ECONOMICS Reference. Bayesian statistical decision theory Econometric models |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=924748 |
| work_keys_str_mv | AT poirierdalej bayesianmodelcomparison AT jeliazkovivan bayesianmodelcomparison |