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https://hdl.handle.net/10419/56184
Kompletter Metadatensatz
DublinCore-Feld | Wert | Sprache |
---|---|---|
dc.contributor.author | Salabasis, Mickael | en |
dc.date.accessioned | 2012-03-28T13:05:37Z | - |
dc.date.available | 2012-03-28T13:05:37Z | - |
dc.date.issued | 2004 | - |
dc.identifier.uri | http://hdl.handle.net/10419/56184 | - |
dc.description.abstract | The full Bayesian treatment of error component models typically relies on data augmentation to produce the required inference. Never stricly necessary a direct approach is always possible though not necessarily practical. The mechanics of direct sampling are outlined and a template for including model uncertainty is described. The needed tools, relying on various Markov chain Monte Carlo techniques, are developed and direct sampling, with and without effect selection, is illustrated. | en |
dc.language.iso | eng | en |
dc.publisher | |aStockholm School of Economics, The Economic Research Institute (EFI) |cStockholm | en |
dc.relation.ispartofseries | |aSSE/EFI Working Paper Series in Economics and Finance |x565 | en |
dc.subject.jel | C11 | en |
dc.subject.jel | C33 | en |
dc.subject.jel | C63 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | Bayesian panel regression | en |
dc.subject.keyword | parametric covariance | en |
dc.subject.keyword | model selection | en |
dc.subject.stw | Bayes-Statistik | en |
dc.subject.stw | Panel | en |
dc.subject.stw | Nichtparametrisches Verfahren | en |
dc.subject.stw | Theorie | en |
dc.title | Parametric covariance matrix modeling in Bayesian panel regression | - |
dc.type | Working Paper | en |
dc.identifier.ppn | 479830266 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
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