Nonparametric density estimation for nonmixing approximable Stochastic Processes
The author deals with nonparametric density estimation for stochastic processes which satisfy the L ∞-approximability property. He considers a Parzen–Rosenblatt estimator of the density for general stationary L ∞-approximable processes. He states conditions under which it is consistent and investigates its rate of convergence. Finally, he applies his results to general nonmixing linear processes and nonmixing nonlinear autoregressive processes.
KeywordsNonparametric density estimation Nonmixing processes Near Epoch Dependence Linear processes Autoregressive processes
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