Concentration of empirical distribution functions with applications to non-i.i.d. models
Bobkov, S.G. ; Götze, F.
Bernoulli, Tome 16 (2010) no. 1, p. 1385-1414 / Harvested from Project Euclid
The concentration of empirical measures is studied for dependent data, whose joint distribution satisfies Poincaré-type or logarithmic Sobolev inequalities. The general concentration results are then applied to spectral empirical distribution functions associated with high-dimensional random matrices.
Publié le : 2010-11-15
Classification:  empirical measures,  logarithmic Sobolev inequalities,  Poincaré-type inequalities,  random matrices,  spectral distributions
@article{1290092911,
     author = {Bobkov, S.G. and G\"otze, F.},
     title = {Concentration of empirical distribution functions with applications to non-i.i.d. models},
     journal = {Bernoulli},
     volume = {16},
     number = {1},
     year = {2010},
     pages = { 1385-1414},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1290092911}
}
Bobkov, S.G.; Götze, F. Concentration of empirical distribution functions with applications to non-i.i.d. models. Bernoulli, Tome 16 (2010) no. 1, pp.  1385-1414. http://gdmltest.u-ga.fr/item/1290092911/