Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1017928823619
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dc.titleAsymptotics for wavelet based estimates of piecewise smooth regression for stationary time series
dc.contributor.authorTruong, Y.K.
dc.contributor.authorPatil, P.N.
dc.date.accessioned2014-10-28T05:10:27Z
dc.date.available2014-10-28T05:10:27Z
dc.date.issued2001
dc.identifier.citationTruong, Y.K., Patil, P.N. (2001). Asymptotics for wavelet based estimates of piecewise smooth regression for stationary time series. Annals of the Institute of Statistical Mathematics 53 (1) : 159-178. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1017928823619
dc.identifier.issn00203157
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105031
dc.description.abstractWavelet 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1023/A:1017928823619
dc.sourceScopus
dc.subjectConvergence rate
dc.subjectDensity estimation
dc.subjectNonparametric regression
dc.subjectPiecewise-smoothness
dc.subjectWavelet
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1023/A:1017928823619
dc.description.sourcetitleAnnals of the Institute of Statistical Mathematics
dc.description.volume53
dc.description.issue1
dc.description.page159-178
dc.description.codenAISXA
dc.identifier.isiut000167624700012
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