Mean square error for histograms when estimating Radon-Nikodym derivatives.
Minimax results for estimating integrals of analytic processes
The problem of predicting integrals of stochastic processes is considered. Linear estimators have been constructed by means of samples at N discrete times for processes having a fixed Hölderian regularity s > 0 in quadratic mean. It is known that the rate of convergence of the mean squared error is of order N-(2s+1). In the class of analytic processes Hp, p ≥ 1, we show that among all estimators, the linear ones are optimal. Moreover, using optimal coefficient estimators derived through...
Minimax results for estimating integrals of analytic processes
Mixed parametrization for curved exponential models in homogeneous Markov processes with a finite state space.
Modèles statistiques et systèmes standards de processus de vraisemblance
Multilinear Estimation of Skewness and Kurtosis in Linear Models.