François Portier

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I am an Assistant Professor at Telecom ParisTech within the department IDS (Image, data, signal).
I am organizing with Anne Sabourin the seminar of Probability and Statistics.

Contact
  • TELECOM ParisTech,
  • 46, rue Barrault, 
  • 75634 Paris Cedex 13, France 
  • Office: E 302
  • Phone: +33 1 45 81 77 03 
                     
francois.portier_gmail_com



My main research topic is semi-parametric statistics. I am interested in parsimonious regression models that allow to reduce the dimension of the covariates without loss of information. The aim is to study algorithms that compute such a reduction. Typical applications are when the number of covariates is too large to be handled by nonparametric methods (>4 is often too much) or simply when none parametric model is available. I am also interested in other semi-parametric problems arising from copula modelling or survival analysis (
CURE models).

I received my Ph.D. from Université de Rennes 1, within the lab IRMAR, under the supervision of Bernard Delyon (defended in July 2013). 


New Papers.

Integral estimation based on Markovian design. With Romain Azais and Bernard Delyon. PDF

On the weak convergence of the empirical conditional copula under a simplifying assumption. With Johan Segers. PDF

Papers.

Efficiency and bootstrap in the promotion time cure model. Accepted in Bernoulli. With Anouar El Ghouch and Ingrid Van Keilegom. 2017. PDF

On the asymptotics of Z-estimators indexed by the objective functions. Electronic Journal of Statistics. 2016. PDF

An empirical process view of inverse regression. Scandinavian Journal of Statistics. 2016. PDF

Integral approximation by kernel smoothing.
Bernoulli. 2016. With Bernard Delyon. PDF


Bootstrap testing of the rank of a matrix via least squared constrained estimation.
Journal of the American Statistical Association. 2014. With Bernard Delyon. PDF

Optimal function: A new approach for covering the central subspace.
Journal of Multivariate Analysis. 2013. 
With Bernard Delyon. PDF



Thesis.
Réduction de la dimension en régression. PDF


Other Links.
A nice blog about statistics, actuarial sciences and R, 
more about the wind in Bretagne.