Category Archives: Conferences

Partager la donnée : une question de confiance ?

Demain, les Rendez-vous Parlementaires de Bretagne sur l’Economie Numérique vont se poursuivre l’après midi, à partir de 14H dans les locaux de la French Tech Rennes-Saint Malo. Un groupe de travail autour de Partager la donnée : une question de confiance ? sera organisé, animé par Simon, avec une trentaine de participants venus du monde de l’entreprise mais aussi de la recherche, du milieu associatif et bien sur des élus de Rennes Métropole. A suivre donc….

La donnée, pierre angulaire de notre économie

Jeudi, je participerais aux Rendez-vous Parlementaires de Bretagne sur l’Economie Numérique,

où on m’a demandé de parler de données. Je dois avoir une quinzaine de minutes, mais comme toujours j’ai prévu pour 2 heures d’exposé. Les slides sont maintenant en ligne, et je me suis dis que je pourrais faire un billet pour détailler le fond de mon propos,

Continue reading La donnée, pierre angulaire de notre économie

Breizh Camp, Economics with Computers

I have been invited, as keynote speaker, at the 6th BreizhCamp, organized in Rennes, from March 23rd till March 25th, “la conférence des développeurs du grand ouest” as they call it. I am deeply honored, since it is a huge conference… The organizing committee asked me to give a (brief) talk on data, and big data. But data is just the visible tip of the iceberg, and I cannot talk about data without mentioning algorithms. So I will try to talk about algorithmics, econometrics, machine learning, and data (and big data, of course).

Slides are now online… More to come in the next days…

Niort, Data Day

Lundi et mardi, je serais à Niort où la MAIF organise un Data Day avec plusieurs conférences (tables rondes) autour de la donnée

L’arrivée du digital créée de nouvelles opportunités, de nouveaux besoins, et de nouveaux risques. Dans ce contexte fortement évolutif et très complexe comment les personnes que nous sommes vont-ils évoluer autour de l’information de son usage et de sa gouvernance ? Quelles tendances peut-on observer ? Quelles compétences à quels horizons et pour quelles attentes ?

Multiattribute, Risk and Utility

As discussed already, in June 2016, with Olivier L’Haridon, we will organize a (small) conference, in Rennes, on risk models in a multi-attribute framework. Related to that conference, we have a working group on related topics. At the end of September, I gave a brief survey on multivariate distributions. And yesterday, Olivier gave the first part of survey on multivariate decision making. The second part will be in two weeks,

Who interacts on Twitter during a conference (#JDSLille)

Disclamer: This is a joint post with Avner Bar-Hen, a.k.a. @a_bh, Benjamin Guedj, a.k.a. @bguedj and Nathalie Villa, a.k.a. @Natty_V2

Organised annually since 1970 by the French Society of Statistics (SFdS), the Journées de Statistique (JdS) are the most important scientific event of the French statistical community. More than 400 researchers, teachers and practitioners meet at each edition. In 2015, JDS took place in Lille, in France.

SFdS regularly tweets (with the account @Statfr) and for the first year a live-tweet was organized durind JdS. The Hashtag was #JDSLille. The aim of this post is a (brief) statistical analysis of the live-tweet.

Continue reading Who interacts on Twitter during a conference (#JDSLille)

Probit Transformation for Nonparametric Kernel Estimation of the Copula Density, Lille

This Monday I will be in Lille to give a talk at the Journées de Statistiques. The talk will be based on the joint work with Gery Geenens and Davy Paindaveine, on Probit transformation for nonparametric kernel estimation of the copula density”. The papier can be found online, on http://arxiv.org/abs/1404.4414

Copula modelling has become ubiquitous in modern statistics. Here, the problem of nonparametrically estimating a copula density is addressed. Arguably the most popular nonparametric density estimator, the kernel estimator is not suitable for the unit-square-supported copula densities, mainly because it is heavily affected by boundary bias issues. In addition, most common copulas admit unbounded densities, and kernel methods are not consistent in that case. In this paper, a kernel-type copula density estimator is proposed. It is based on the idea of transforming the uniform marginals of the copula density into normal distributions via the probit function, estimating the density in the transformed domain, which can be accomplished without boundary problems, and obtaining an estimate of the copula density through back-transformation. Although natural, a raw application of this procedure was, however, seen not to perform very well in the earlier literature. Here, it is shown that, if combined with local likelihood density estimation methods, the idea yields very good and easy to implement estimators, fixing boundary issues in a natural way and able to cope with unbounded copula densities. The asymptotic properties of the suggested estimators are derived, and a practical way of selecting the crucially important smoothing parameters is devised. Finally, extensive simulation studies and a real data analysis evidence their excellent performance compared to their main competitors.”

The slides are available on Dropbox (it is a 54Mo file with animated pictures, that do not appear on the version below).