[Statlist] Next talk: Tuesday, December 13, 2016 with William Aeberhard, Dalhousie University, Halifax

[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:

Tuesday, December 13, 2016 at 15.15h  ETH Zurich HG G19.2G E 41
with William Aeberhard, Dalhousie University, Halifax
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Title:

Robust fitting of state-space models with application to fish stock assessments<https://www.math.ethz.ch/sfs/news-and-events/research-seminar.html?s=hs16#e_9769>


Abstract:

State-space models (SSMs) encompass a wide range of popular models encountered in various fields such as mathematical finance, control engineering and ecology. SSMs are essentially characterized by a hierarchical structure, with latent (unobserved) variables governed by Markovian dynamics. Classical estimation of fixed parameters in these models, for instance by maximizing an approximated marginal likelihood, is known to be highly sensitive to the correct specification of the model. This sensitivity is all the more so problematic since assumptions about latent variables cannot be verified by the data analyst. Motivated by the highly non-linear models used for fish stock assessments, we introduce robust estimators for general SSMs which remain stable under deviations from the assumed model. The implementation relies on Laplace's method, where automatic differentiation allows the user to robustly fit such a model in a matter of minutes. A real-life fish stock assessment example illustrates the reliable inference these estimators can yield and how robustness weights can be used as diagnostic tools.


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

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