[Statlist] Next talk: Thursday, 13.06.2019, with Andreas Buja, University of Pennsylvania

[Maurer Letizia]

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ETH and University of Zurich

Organisers:

Proff. P. Bühlmann - L. Held - T. Hothorn - M. Maathuis -
N. Meinshausen - S. van de Geer - M. Wolf

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We are glad to announce the following talk:

Thursday, 13.06.2019, at 15.15 h  ETH Zurich HG G19.1
with Andreas Buja, University of Pennsylvania

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Title:

Models as Approximations -- A Model-Free Theory of Parametric Regression

Abstract:

In this talk we will rethink what we do when we apply regression to data. We will do so without assuming the correctness of a fitted regression model. We will think of the parameters of the fitted model as statistical functionals, here called "regression functionals," which apply to largely arbitrary (X,Y) distributions. In this view a fitted model is an approximation, not a "data generating process." A natural question is whether such an assumption-lean framework lends itself to a useful statistical theory. Indeed it does: It is possible to (1) define a notion of well-specification for regression functionals that replaces the notion of correct specification of models, (2) create a well-specification diagnostic for regression functionals based on reweighting the data, (3) prove insightful Central Limit Theorems, (4) clear up the misconception that "model bias" generates biased estimates,(5) exhibit standard errors of the plug-in/sandwich type as limiting cases of the pairs- or (X,Y)-bootstrap, and (6) provide theoretical heuristics to indicate that pairs-bootstrap standard errors may generally be more stable than sandwich standard errors.

This abstract is also to be found under the following link: http://stat.ethz.ch/events/research_seminar

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ETH Zürich
Letizia Maurer
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Departement Mathematik
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cletizia at ethz.ch<mailto:cletizia at ethz.ch>




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