This paper deals with techniques which permit one to obtain the range of a posterior expectation through a sequence of linear optimizations. In the contexts of Bayesian robustness, the lenearization agorithm plays a fundamental role Its mathematical aspects and its connection with fractional programming procedures are reviewed and a few instances of its broad applicability are listed. At the end, some alternative approaches are briefly discussed.

Linearization tecnhiques in Bayesian robustness / Lavine, M.; PERONE PACIFICO, M.; SALINETTI BRACCIALI, G.; L., Tardella. - (2000), pp. 261-272.

Linearization tecnhiques in Bayesian robustness

PERONE PACIFICO M.;
2000

Abstract

This paper deals with techniques which permit one to obtain the range of a posterior expectation through a sequence of linear optimizations. In the contexts of Bayesian robustness, the lenearization agorithm plays a fundamental role Its mathematical aspects and its connection with fractional programming procedures are reviewed and a few instances of its broad applicability are listed. At the end, some alternative approaches are briefly discussed.
978-0387988665
Linearization tecnhiques in Bayesian robustness / Lavine, M.; PERONE PACIFICO, M.; SALINETTI BRACCIALI, G.; L., Tardella. - (2000), pp. 261-272.
File in questo prodotto:
File Dimensione Formato  
0P-ISBN-0-387-98866-1-Springer-Lecture-Notes-2001-Lavine-Perone-Pacifico-Salinetti-Tardella.pdf

Solo gestori archivio

Tipologia: Versione dell'editore
Licenza: DRM non definito
Dimensione 2.59 MB
Formato Adobe PDF
2.59 MB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11385/182668
Citazioni
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact