Author： Truong Y.K.
Publisher： Springer Publishing Company
ISSN： 0020-3157
Source： Annals of the Institute of Statistical Mathematics, Vol.53, Iss.1, 2001-03, pp. : 159-178
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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.
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