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Lithuanian Mathematical Journal

, Volume 59, Issue 2, pp 276–293 | Cite as

Wavelet estimation in time-varying coefficient models

  • Xingcai ZhouEmail author
  • Beibei Ni
  • Chunhua Zhu
Article
  • 40 Downloads

Abstract

The paper is concerned with the estimation of a time-varying coefficient time series model, which is used to characterize the nonlinearity and trending phenomenon. We develop the wavelet procedures to estimate the coefficient functions and the error variance. We establish asymptotic properties of the proposed wavelet estimators under the α-mixing conditions and without specifying the error distribution. These results can be used to make asymptotically valid statistical inference.

Keywords

time-varying coefficient model wavelet estimation convergence rate asymptotic normality 

MSC

primary 62G05 secondary 60G07 

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References

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Statistics and Data ScienceNanjing Audit UniversityNanjingChina

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