arXiv · 1902.10381
Adaptation for nonparametric estimators of locally stationary processes
Abstract
Two adaptive bandwidth selection methods for nonparametric estimators in locally stationary processes are proposed. We investigate a cross validation approach and a method based on contrast minimization and derive asymptotic properties of both methods. The results are applicable for different statistics under a broad setting of locally stationarity including nonlinear processes. At the same time we deepen the general framework for local stationarity based on stationary approximations. For example a general Bernstein inequality is derived for such processes. A simulation study performed on the covariance function and more complicated functionals shows that both adaptation methods work well.
Explore related subjects
Keep this discovery
Rainer Dahlhaus, Stefan Richter. 2019-02-27. Adaptation for nonparametric estimators of locally stationary processes. https://arxiv.org/abs/1902.10381
Cite the original work for its findings. Save a collection to share your selection of sources.