[Statlist] Next talk: Friday, 28.09.2018, with Brendan McCabe, University of Liverpool

[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:

Friday, 28.09.2018, at 15.15 h  ETH Zurich HG G19.1
with Brendan McCabe, University of Liverpool

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Title:

Approximate Bayesian Forecasting<https://www.math.ethz.ch/sfs/news-and-events/research-seminar.html?s=hs18#e_12110>

Abstract:

Approximate Bayesian Computation (ABC) has become increasingly prominent as a method for conducting parameter inference in a range of challenging statistical problems, most notably those characterized by an intractable likelihood function. In this paper, we focus on the use of ABC not as a tool for parametric inference, but as a means of generating probabilistic forecasts; or for conducting what we refer to as ‘approximate Bayesian forecasting’. The four key issues explored are:
i) the link between the theoretical behavior of the ABC posterior and that of the ABC-based predictive;
ii) the use of proper scoring rules to measure the (potential) loss of forecast accuracy when using an approximate rather than an exact predictive;
iii) the performance ofapproximate Bayesian forecasting in state space models; and
iv) the use of forecasting criteria to inform the selection of ABC summaries in empirical settings. The primary finding of the paper is that ABC can provide a computationally efficient means of generating probabilistic forecasts that are nearly identical to those produced by the exact predictive, and in a fraction of the time required to produce predictions via an exact methods.

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

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