In this paper, we consider a problem of estimation. The model is the same as in the first part of this paper. Our goal is to construct an adaptive estimator over a family of Hölder spaces if an additionnal information is known. Typically, we suppose that the "effective smoothness parameter" is known. A knowledge of this type is to be understood as follows: If you want to estimate with a given rate (precision), you have to fix this parameter. We construct an estimator which is minimax over the union of all Hölder spaces defined using this effective smoothness. This problem is linked to the maxiset theory
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirica...
We present error estimates of a linear fully discrete scheme for a threedimensional mass diffusion ...
We argue that common features of non-parametric estimation appear in parametric cases as well if the...
In this paper, we consider the following problem: We want to estimate a noisy signal. The main probl...
International audienceWe address the problem of adaptive minimax estimation in white Gaus-sian noise...
National audienceWe consider the design of c-optimal experiments for the estimation of a scalar func...
Within Bayesian state estimation, an important effort has been put to incorporate constraints into s...
The difference equations ξk = af(ξk-1) + εk, where (εk) is a square integrable difference martingale...
AbstractIn this paper, we study the problem of nonparametric estimation of the mean and variance fun...
AbstractThe problem of identification of the diffusion coefficient in the partial differential equat...
We consider a model $Y_t=\sigma_t\eta_t$ in which $(\sigma_t)$ is not independent of the noise proce...
International audienceIn this paper, we study the problem of nonparametric estimation of the mean an...
AbstractWe discuss the following problem. Let ∫ab fψj dy = fj + εj, 1 ⩽ j ⩽ n, \̄g3j∗εp = Cjp. Given...
This note is a complement of the paper "Solving BSDE with adaptive control variate". It deals with t...
We consider best approximation problems in a nonlinear subset ℳ of a Banach space of functions (,∥•∥...
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirica...
We present error estimates of a linear fully discrete scheme for a threedimensional mass diffusion ...
We argue that common features of non-parametric estimation appear in parametric cases as well if the...
In this paper, we consider the following problem: We want to estimate a noisy signal. The main probl...
International audienceWe address the problem of adaptive minimax estimation in white Gaus-sian noise...
National audienceWe consider the design of c-optimal experiments for the estimation of a scalar func...
Within Bayesian state estimation, an important effort has been put to incorporate constraints into s...
The difference equations ξk = af(ξk-1) + εk, where (εk) is a square integrable difference martingale...
AbstractIn this paper, we study the problem of nonparametric estimation of the mean and variance fun...
AbstractThe problem of identification of the diffusion coefficient in the partial differential equat...
We consider a model $Y_t=\sigma_t\eta_t$ in which $(\sigma_t)$ is not independent of the noise proce...
International audienceIn this paper, we study the problem of nonparametric estimation of the mean an...
AbstractWe discuss the following problem. Let ∫ab fψj dy = fj + εj, 1 ⩽ j ⩽ n, \̄g3j∗εp = Cjp. Given...
This note is a complement of the paper "Solving BSDE with adaptive control variate". It deals with t...
We consider best approximation problems in a nonlinear subset ℳ of a Banach space of functions (,∥•∥...
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirica...
We present error estimates of a linear fully discrete scheme for a threedimensional mass diffusion ...
We argue that common features of non-parametric estimation appear in parametric cases as well if the...