Nonparametric Statistics for Stochastic Processes Estimation and Prediction [Paperback]

Synopsis.- 1. Inequalities for mixing processes.- 2. Density estimation for discrete time processes.- 3. Regression estimation and prediction for discrete time processes.- 4. Kernel density estimation for continuous time processes.- 5. Regression estimation and prediction in continuous time.- 6. The local time density estimator.- 7. Implementation of nonparametric method and numerical applications.- References.Written by one of the leading statisticians in France, this revision offers new material on the theory and applications of nonparametric statistics for stochastic processes.Springer Book Archives