This paper is first devoted to study an adaptive wavelet based estimator of the long memory parameter for linear processes in a general semi-parametric frame. This is an extension of Bardet et al. (2008) which only concerned Gaussian processes. Moreover, the definition of the long memory parameter estimator is modified and asymptotic results are improved even in the Gaussian case. Finally an ad...

Cluster-Weighted Modeling, a mixture density estimator around local models, is presented as a framework for the analysis, prediction and characterization of non-linear time series. First architecture, model estimation and characterization formalisms are introduced. The characterization tools include estimator uncertainty, predictor uncertainty and the correlation dimension of the data set. In t...

We prove convergence and quasi-optimal complexity of an adaptive finite element algorithm on triangular meshes with standard mesh refinement. Our algorithm is based on an adaptive marking strategy. In each iteration, a simple edge estimator is compared to an oscillation term and the marking of cells for refinement is done according to the dominant contribution only. In addition, we introduce an...

Off-policy evaluation (OPE) aims to accurately evaluate the performance of counterfactual policies using only offline logged data. Although many estimators have been developed, there is no single estimator that dominates others, because estimators' accuracy can vary greatly depending on a given OPE task such as policy, number actions, and noise level. Thus, data-driven selection problem becomin...