Patrimony

The Louis Bachelier Group's patrimony has been defined as all the publications produced by academic researchers thanks to Group funding (ILB, FdR, IEF, Labex) or via the use of EquipEx data (BEDOFIH, EUROFIDAI).


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Nonparametric regression and spatially inhomogeneous information.

Adaptive estimation, Asymptotically sharp estimation, Degenerate design, Design aléatoire, Design dégénéré, Estimation adaptative, Estimation asymptotiquement exacte, Estimation à noyaux, Kernel estimation, Lepski method, Local polynomial estimation, Minimax risk, Méthode de Lepski, Nonparametric regression, Optimal recovery, Polynômes locaux, Random design, Risque minimax, Régression non-paramétrique

Nonparametric estimation in a regression model with additive and multiplicative noise.

Multiplicative regression models, Nonparametric frontier, Nonparametric regression, Rates of convergence, Wavelets

Efficiency of the V -Fold Model Selection for Localized Bases.

Heteroscedastic noise, Model selection, Nonparametric regression, Random design, V-fold cross-validation, V-fold penalization, Wavelets

Linear wavelet estimation in regression with additive and multiplicative noise.

Multiplicative noise, Nonparametric regression, Rates of convergence, Wavelets

Nonparametric estimation in a regression model with additive and multiplicative noise.

Multiplicative regression models, Nonparametric frontier, Nonparametric regression, Rates of convergence, Wavelets

Linear wavelet estimation of the derivatives of a regression function based on biased data.

Besov balls, Biased data, Deriva-tives function estimation, Nonparametric regression, Wavelets

On the pointwise mean squared error of a multidimensional term-by-term thresholding wavelet estimator.

And phrases Pointwise mean squared error, Density estimation, Nonparametric regression, Wavelet methods

Slope heuristics and V-Fold model selection in heteroscedastic regression using strongly localized bases.

Cross-validation, Heteroscedastic noise, Model selection, Nonparametric regression, Random design, Wavelets

Linear Wavelet Estimation in Regression with Additive and Multiplicative Noise.

Multiplicative noise, Nonparametric regression, Rates of convergence, Wavelets

Optimal selection of localized basis models in heteroskedastic regression.

Cross-validation, Heteroscedastic noise, Localised basis, Model selection, Nonparametric regression, Oracle inequality, Slope heuristics, Wavelets