[Forum SIS] Seminario prof.ssa Ventura 21/2/2020 h. 14.15

[Dip. Scienze Statistiche - Mi]

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Dipartimento di Scienze Statistiche - Università Cattolica del Sacro Cuore, Milano

AVVISO DI SEMINARIO
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Venerdì 21 Febbraio dalle ore 14,15

in Aula G.053



Università Cattolica del Sacro Cuore - Milano

Largo Gemelli, 1


Prof.ssa Laura VENTURA, Università degli Studi di Padova

Bayesian posterior distributions
from estimating functions


Abstract:
We discuss the use of estimating equations in order to compute a posterior distribution in two frameworks.
1) Standard Bayesian analyses can be difficult to perform when the full likelihood, and consequently the full posterior distribution, is too complex and difficult to specify or if robustness with respect to data or to model misspecifications is required. In these situations, we suggest to resort to a posterior distribution for the parameter of interest based on unbiased estimating equations, which include as special instances M-estimating functions and proper scoring rules. We show that the posterior distribution can be derived analytically or by approximate Bayesian computation methods.
2) Consider Bayesian inference when the prior distribution is known only through its first derivative (typically with multidimensional parameters and objective priors, e.g. matching priors). In this case it is only possibile to evaluate the first derivative of the log-posterior. In this framework, we propose two methods to derive a posterior distribution for a parameter of interest using a Rao score statistic or a local Taylor approximation of the log-posterior and its first derivative.




Segreteria Organizzativa:

Barbara Villa
Funzione Ricerca
Dipartimento di Scienze statistiche
Edificio Lanzone, 18
Dip.scienzestatistiche at unicatt.it<mailto:Dip.scienzestatistiche at unicatt.it>
Tel. +39 02 7234 2647
http://dipartimenti.unicatt.it/scienze_statistiche


Università Cattolica del Sacro Cuore
Largo Gemelli 1, 20123 Milano
www.unicatt.it<http://www.unicatt.it/>


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