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5 papers · 2 filters
Kernel Inverse Regression for spatial random fields
Jean-Michel Loubes, Anne-Françoise Yao
In this paper, we propose a dimension reduction model for spatially dependent variables. Namely, we investigate an extension of the \emph{inverse regression} method under strong mi…
Non parametric estimation of the structural expectation of a stochastic increasing function
Jean-François Dupuy, Jean-Michel Loubes, Elie Maza
This article introduces a non parametric warping model for functional data. When the outcome of an experiment is a sample of curves, data can be seen as realizations of a stochasti…
A deconvolution approach to estimation of a common shape in a shifted curves model
Jérémie Bigot, Sébastien Gadat
This paper considers the problem of adaptive estimation of a mean pattern in a randomly shifted curve model. We show that this problem can be transformed into a linear inverse prob…
Maximum likelihood estimation in a partially observed stratified regression model with censored data
Amélie Detais, Jean-François Dupuy
The stratified proportional intensity model generalizes Cox's proportional intensity model by allowing different groups of the population under study to have distinct baseline inte…
Maxisets for Model Selection
Florent Autin, Erwan Le Pennec, Jean-Michel Loubes +1
We address the statistical issue of determining the maximal spaces (maxisets) where model selection procedures attain a given rate of convergence. By considering first general dict…