Abstract
Wavelet methods are used to estimate density and (auto-) regression functions that are possibly discontinuous. For stationary time series that satisfy appropriate mixing conditions, we derive mean integrated squared errors (MISEs) of wavelet-based estimators. In contrast to the case for kernel methods, the MISEs of wavelet-based estimators are not affected by the presence of discontinuities in the curves. Applications of this approach to problems of identification of nonlinear time series models are discussed.
Original language | English |
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Pages (from-to) | 159-178 |
Number of pages | 20 |
Journal | Institute of Statistical Mathematics. Annals |
Volume | 53 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2001 |
Keywords
- density estimation
- piecewise-smoothness
- convergence rate
- nonparametric regression
- wavelet