[Statlist] Statistics Seminar, December 2 2010 at 15h15

Schaffner Portillo Maroussia m@rou@@|@@@ch@||nerport|||o @end|ng |rom ep||@ch
Tue Nov 23 09:47:41 CET 2010


STATISTICS SEMINAR

Thursday, December 2, 2010 - 15h15

Room MA A3 30 - EPFL

Prof. Helmut Rieder
Universit�t Bayreuth

will be speaking on :


Connections between Robustness and Semiparametrics



Abstract:
Apart from their similar historical origin and common locally asymptotically normal framework, the relation of robust and semiparametric statistics may be clarified by an investigation of the following issues: Robustness of adaptive estimators, robust influence curves for semiparametric models with infinite dimensional nuisance parameter, adaptiveness in the sense of Stein (1956) of robust neighborhood models with respect to a nuisance parameter, interpretation of gross error deviations as the value of an infinite dimensional nuisance parameter, asymptotic normality of adaptive and robust estimators. We spell out the comparison for time series (ARMA, ARCH), semiparametric regression (Cox), and mixture models (Neyman-Scott). Our two fields may further be distinguished by tangent balls in the place of linear tangent spaces. In the context of estimation, an extended semiparametric technique -projection on balls- turns out almost, but not quite, to reproduce optimally robust influence curves. However, a semiparametric saddle point result for testing (even more general) convex tangent sets, based on the projection on the set of di?erences made up by the two sets, does yield asymptotic versions of the robust tests based on least favorable pairs in the sense of Huber-Strassen (1973). Finally, a semiparametric result for tangent cones, as opposed to spaces, leads to an optimal but very unstable estimator and, in particular, renders a concentration bound by Pfanzagl and Wefelmeyer (1982) unattainable.



Best regards.



Maroussia Schaffner Portillo

EPFL-SB-SMAT

Phone: 37922

 http://smat.epfl.ch/seminar/seminar.php


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