[Forum SIS] Webinar of Davide Ferrari @ Unimib

[Federico Camerlenghi]

Dear all,

We are glad to announce the next DEMS Statistics Webinar, organized by the
Department of Economics, Management and Statistics (DEMS) of the University
of Milano - Bicocca.

Speaker: Davide Ferrari, University of Bolzano, Italy

https://dferraristat.wixsite.com/davideferrari

Wednesday, December 16th, 2020, time 13.00 (CET).

Link to attend the event:

https://unimib.webex.com/unimib/onstage/g.php?MTID=ef8293c1e4a8acf16a9f5f78b6285cd01

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Title:

Model selection by sparse composition of estimating equations

Abstract:

This talk introduces a method for selecting high-dimensional models based
on a truncation mechanism to generate sparse estimating equations. Given a
set of low-dimensional estimating equations for the model parameters, a
high-dimensional model is selected by minimizing the distance between a
composite estimating equation and the full likelihood scores subject to a
L1 -type penalty. The proposed strategy reduces the overall model
complexity scores subject to a L1 -type penalty. The proposed strategy
reduces the overall model complexity by dropping the noisy terms in the
estimating equations. Differently from other approaches to model
selection, our penalty involves the inclusion of low-dimensional equations
rather than model parameters; this implies that consistency of the final
parameter estimates remains largely unaffected by the selection mechanism.
The numerical and statistical efficiency final parameter estimates
remain largely unaffected by the selection mechanism. The numerical and
statistical efficiency of the new methodology is illustrated through
examples on simulated and real data.

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More details to attend the webinar:

link to attend:
https://unimib.webex.com/unimib/onstage/g.php?MTID=ef8293c1e4a8acf16a9f5f78b6285cd01

Event number (access code): 174 310 7972
Event password: 16122020

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The webinar is part of the series of DEMS Statistics Webinars organized by
the Department of Economics, Management and Statistics (DEMS) of the
University of Milano - Bicocca. More details can be found here:

https://dems.unimib.it/it/argomento-eventi/seminars/dems-seminars


-- 
Federico Camerlenghi
Assistant Professor RTDb
Department of Economics, Management and Statistics
University of Milano Bicocca, Milano, Italy.
web-page: https://www.unimib.it/federico-camerlenghi
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