Decay of correlations for non Hölderian dynamics. A coupling approach.
Décomposition des processus aléatoires, une comparaison entre les méthodes factorielles et l'analyse spectrale
Density estimation for one-dimensional dynamical systems
In this paper we prove a Central Limit Theorem for standard kernel estimates of the invariant density of one-dimensional dynamical systems. The two main steps of the proof of this theorem are the following: the study of rate of convergence for the variance of the estimator and a variation on the Lindeberg–Rio method. We also give an extension in the case of weakly dependent sequences in a sense introduced by Doukhan and Louhichi.
Density Estimation for One-Dimensional Dynamical Systems
In this paper we prove a Central Limit Theorem for standard kernel estimates of the invariant density of one-dimensional dynamical systems. The two main steps of the proof of this theorem are the following: the study of rate of convergence for the variance of the estimator and a variation on the Lindeberg–Rio method. We also give an extension in the case of weakly dependent sequences in a sense introduced by Doukhan and Louhichi.
Detection of transient change in mean – a linear behavior inside epidemic interval
A procedure for testing occurrance of a transient change in mean of a sequence is suggested where inside an epidemic interval the mean is a linear function of time points. Asymptotic behavior of considered trimmed maximum-type test statistics is presented. Approximate critical values are obtained using an approximation of exceedance probabilities over a high level by Gaussian fields with a locally stationary structure.
Determinism and martingale decompositions of strictly stationary random processes
Die Anzahl der lokalen Maximalstellen eines stationären Gauszschen Prozesses.
Dimension and Entropy of a Non-ergodic Markovian Process and its Relation to Rademacher Riesz Products.
Dirichlet problem associated with a random quasilinear operator in a random domain
Disaggregation of long memory processes on class.
Discrete approximation in the innovation theory of second-order continuous processes.