Wavelet-M-Estimation for Time-Varying Coefficient Time Series Models

Abstract EN

This paper proposes wavelet-M-estimation for time-varying coefficient time series models by using a robust-type wavelet technique, which can adapt to local features of the time-varying coefficients and does not require the smoothness of the unknown time-varying coefficient.

The wavelet-M-estimation has the desired asymptotic properties and can be used to estimate conditional quantile and to robustify the usual mean regression.

Under mild assumptions, the Bahadur representation and the asymptotic normality of wavelet-M-estimation are established.