New Results on Time Series and their Statistical Applications
Séries chronologiques: nouveaux résultats et applications statistiques
Séries chronologiques: nouveaux résultats et applications statistiques
HYBRID CONFERENCE / 14 - 18 September 2020
(With abstracts)
Discussion rooms will be available to registered conference participants via the link below. Your access code to the rooms is provided by the organizers.
This page is accessible with a password issued by CIRM.
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Organizing Committee
Jean-Marc Bardet (Université Paris 1 Panthéon-Sorbonne) Idris Eckley (Lancaster University) Konstantinos Fokianos (University of Cyprus) Michael H. Neumann (Friedrich Schiller University Jena) Anne Philippe (Université de Nantes) Scientific Committee Paul Doukhan (Université de Cergy-Pontoise) Liudas Giraitis (Queen Mary University of London) Suhasini Subba Rao (Texas A&M University) Olivier Winterberger (Sorbonne Université) Statistical modeling and analysis of time series data has been traditionally based on the assumption of stationarity and/or low dimensionality. Nowadays technology calls for abandoning such assumptions and require the development of new and more sophisticated statistical methods. For instance, the assumption of stationarity, which has dominated most of time series literature, is restricted and cannot be justified for many applications. Additionally, study of long-range dependent processes revealed concrete distinctions between stationary and non-stationary processes. And it is quite common in practice to observe time series which exhibit trend, periodic behavior and require additionally inclusion of covariates.
These new applications are developing very quickly and are found in diverse research areas. Based on this fact and motivated by these challenging problems, we propose to organize a conference whose main theme is New results on time series and their statistical applications. We are quite confident that such a meeting will bring together researchers from all over the world to discuss and exchange ideas about future research directions and initiatives. In particular, we aim on a program that covers many ”hot” research topics like: • Locally-stationary and non-stationary time series; • High-dimensional time series; • Change-point methods and switching processes; • Long-range dependent time series; • New limit theorems on means and extremes; • New concentration inequalities and model selection; • New measures of dependence; • New statistical applications on reall datasets |
Speakers
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