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.
Lavine, M.; Perone Pacifico, Marco; SALINETTI BRACCIALI, G.; L., Tardella. (2000). Linearization tecnhiques in Bayesian robustness. In D. Rios Insua and F. Ruggeri (Eds.), Robust Bayesian Analysis - Lecture Notes in Statistics (pp. 261-272). Springer Verlag. Isbn: 978-0387988665.
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.
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