Geodesic
On some recent advances on high dimensional Bayesian statistics
Nicolas Chopin1 ; Sébastien Gadat2 ; Benjamin Guedj3 ; Arnaud Guyader4 ; Elodie Vernet5
1 ENSAE, Malakoff, France,
2 Toulouse School of Economics (Université Toulouse I Capitole), Toulouse, France,
3 MODAL project-team, Inria Lille - Nord Europe, Villeneuve d’Ascq, France,
4 LSTA, Université Pierre et Marie Curie, Paris, France & Projet ASPI, Inria, Rennes, France,
5 Université Paris-Sud, Orsay, France,
ESAIM. Proceedings, Tome 51 (2015), pp. 293-319 Cet article a éte moissonné depuis la source EDP Sciences

Voir la notice de l'article

This paper proposes to review some recent developments in Bayesian statistics for high dimensional data. After giving some brief motivations in a short introduction, we describe new advances in the understanding of Bayes posterior computation as well as theoretical contributions in non parametric and high dimensional Bayesian approaches. From an applied point of view, we describe the so-called sqmc particle method to compute posterior Bayesian law, and provide a nonparametric analysis of the widespread abc method. On the theoretical side, we describe some recent advances in Bayesian consistency for a nonparametric hidden Markov model as well as new pac-Bayesian results for different models of high dimensional regression.
DOI : 10.1051/proc/201551016

Nicolas Chopin 1 ; Sébastien Gadat 2 ; Benjamin Guedj 3 ; Arnaud Guyader 4 ; Elodie Vernet 5

1 ENSAE, Malakoff, France,
2 Toulouse School of Economics (Université Toulouse I Capitole), Toulouse, France,
3 MODAL project-team, Inria Lille - Nord Europe, Villeneuve d’Ascq, France,
4 LSTA, Université Pierre et Marie Curie, Paris, France & Projet ASPI, Inria, Rennes, France,
5 Université Paris-Sud, Orsay, France, 
@article{EP_2015_51_a16,
     author = {Nicolas Chopin and S\'ebastien Gadat and Benjamin Guedj and Arnaud Guyader and Elodie Vernet},
     title = {On some recent advances on high dimensional {Bayesian} statistics},
     journal = {ESAIM. Proceedings},
     pages = {293--319},
     year = {2015},
     volume = {51},
     doi = {10.1051/proc/201551016},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.1051/proc/201551016/}
}
TY  - JOUR
AU  - Nicolas Chopin
AU  - Sébastien Gadat
AU  - Benjamin Guedj
AU  - Arnaud Guyader
AU  - Elodie Vernet
TI  - On some recent advances on high dimensional Bayesian statistics
JO  - ESAIM. Proceedings
PY  - 2015
SP  - 293
EP  - 319
VL  - 51
UR  - http://geodesic.mathdoc.fr/articles/10.1051/proc/201551016/
DO  - 10.1051/proc/201551016
LA  - en
ID  - EP_2015_51_a16
ER  - 
%0 Journal Article
%A Nicolas Chopin
%A Sébastien Gadat
%A Benjamin Guedj
%A Arnaud Guyader
%A Elodie Vernet
%T On some recent advances on high dimensional Bayesian statistics
%J ESAIM. Proceedings
%D 2015
%P 293-319
%V 51
%U http://geodesic.mathdoc.fr/articles/10.1051/proc/201551016/
%R 10.1051/proc/201551016
%G en
%F EP_2015_51_a16
Nicolas Chopin; Sébastien Gadat; Benjamin Guedj; Arnaud Guyader; Elodie Vernet. On some recent advances on high dimensional Bayesian statistics. ESAIM. Proceedings, Tome 51 (2015), pp. 293-319. doi: 10.1051/proc/201551016

Cité par Sources :