63 citations · 113 across the 8 of their papers we have counts for
8 papers
Inference post region selection
Dominique Bontemps, François Bachoc, Pierre Neuvial
Post-selection inference consists in providing statistical guarantees, based on a data set, that are robust to a prior model selection step on the same data set. In this paper, we…
Bayesian methods in the Shape Invariant Model (II): Identifiability and posterior contraction rates on functional spaces
Dominique Bontemps, Sebastien Gadat
In this paper, we consider the so-called Shape Invariant Model which stands for the estimation of a function f0 submitted to a random translation of law g0 in a white noise model.…
Bayesian methods in the Shape Invariant Model (I): Posterior contraction rates on probability measures
Dominique Bontemps, Sebastien Gadat
In this paper, we consider the so-called Shape Invariant Model which stands for the estimation of a function f0 submitted to a random translation of law g0 in a white noise model.…
Bayesian posterior consistency in the functional randomly shifted curves model
Dominique Bontemps, Sébastien Gadat
In this paper, we consider the so-called Shape Invariant Model which stands for the estimation of a function submitted to a random translation of law in a white noise m…
About adaptive coding on countable alphabets
Dominique Bontemps, Stéphane Boucheron, Elisabeth Gassiat
This paper sheds light on universal coding with respect to classes of memoryless sources over a countable alphabet defined by an envelope function with finite and non-decreasing ha…
Bernstein von Mises Theorems for Gaussian Regression with increasing number of regressors
Dominique Bontemps
This paper brings a contribution to the Bayesian theory of nonparametric and semiparametric estimation. We are interested in the asymptotic normality of the posterior distribution…