Nonparametric Statistics for Stochastic Processes

Inhaltsverzeichnis

• 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.