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Ventura, Laura and Cabras, Stefano and Racugno, Walter (2009) Default prior distributions from quasi- and quasi-profile likelihoods. [Working Paper] WORKING PAPER SERIES, 1/2009 . , PADOVA (Inedito)

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Abstract (english)

In some problems of practical interest, a standard Bayesian analysis can be difficult to perform. This is true, for example, when the class of sampling parametric models is unknown or if robustness with respect to data or to model misspecifications is required. These situations can be usefully handled by using a posterior distribution for the parameter of interest which is based on a pseudo-likelihood function derived from estimating equations, i.e. on a quasi-likelihood, and on a suitable prior distribution.
The aim of this paper is to propose and discuss the construction of a default prior distribution for a scalar parameter of interest to be used together with a quasi-likelihood function. We show that the proposed default prior can be interpreted as a Jeffreys-type prior, since it is proportional to the square-root of the expected information derived from the quasi-likelihood. The frequentist coverage of the credible regions, based on the proposed procedure, is studied through Monte Carlo simulations in the context of robustness theory and of generalized linear models with overdispersion.


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EPrint type:Working Paper
Anno di Pubblicazione:January 2009
Key Words:Estimating equation, Jeffrey’s prior, Matching prior, Nuisance parameter, Pseudo-likelihood, Robustness.
Settori scientifico-disciplinari MIUR:Area 13 - Scienze economiche e statistiche > SECS-S/01 Statistica
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Statistiche
Codice ID:7142
Depositato il:15 Sep 2014 13:28
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