[Forum SIS] webinar di Pierre Jacob per DEMS Bicocca

[Bernardo Nipoti]

Cari colleghi,

vorrei segnalarvi il webinar che Pierre Jacob
<https://sites.google.com/site/pierrejacob/> (Harvard University) terrà
giovedì 4 giugno alle 14.00 per il dipartimento di Economia, Metodi
Quantitativi e Strategie di Impresa dell'Università di Milano Bicocca.

Chiunque fosse interessato a partecipare è pregato di mandarmi una mail
all'indirizzo bernardo.nipoti a unimib.it

*DEMS seminar series: webinar di Pierre Jacob (4 giugno 2020, ore 14.00)*

*Title: *A Gibbs sampler for a class of random convex polytopes.

*Abstract:* We present a Gibbs sampler for the Dempster--Shafer (DS)
approach to statistical inference in the setting of for Categorical
distributions, with arbitrary numbers of categories and observations. The
DS framework extends the Bayesian approach, allows in particular the use of
partial prior information, and yields three-valued uncertainty assessments
(p,q,r) representing probabilities ``for'', ``against'', and ``don't know''
about formal assertions of interest.  However DS gives rise to
computational challenges even in settings as classical as Categorical
distributions for count data.  The proposed algorithm targets the
distribution of a class of random convex polytopes which encapsulate the DS
inference. The sampler relies on an equivalence between the iterative
constraints of the vertex configuration and the non-negativity of cycles in
a fully connected directed graph.

This is joint work with Ruobin Gong, Paul T. Edlefsen, Arthur P. Dempster
and a technical report is available at https://arxiv.org/abs/1910.11953
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