Adaptive estimation of the stationary density of discrete and continuous time mixing processes
Fabienne Comte, Florence Merlevède (2010)
ESAIM: Probability and Statistics
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In this paper, we study the problem of non parametric estimation of the stationary marginal density of an or a -mixing process, observed either in continuous time or in discrete time. We present an unified framework allowing to deal with many different cases. We consider a collection of finite dimensional linear regular spaces. We estimate using a projection estimator built on a data driven selected linear space among the collection. This data driven choice is performed the minimization...