Estimation of Time Series Models via Robust Wavelet Variance

  • Stephane Guerrier University of California, Santa Barbara
  • Roberto Molinari Universite de Geneve
  • Maria-Pia Victoria-Feser Universite de Geneve

Abstract

A robust approach to the estimation of time series models is proposed. Taking from
a new estimation method called the Generalized Method of Wavelet Moments (GMWM)
which is an indirect method based on the Wavelet Variance (WV), we replace the classical
estimator of the WV with a recently proposed robust M-estimator to obtain a robust
version of the GMWM. The simulation results show that the proposed approach can be
considered as a valid robust approach to the estimation of time series and state-space
models.

Published
2014-06-13
How to Cite
Guerrier, S., Molinari, R., & Victoria-Feser, M.-P. (2014). Estimation of Time Series Models via Robust Wavelet Variance. Austrian Journal of Statistics, 43(4), 267-277. https://doi.org/https://doi.org/10.17713/ajs.v43i4.45
Section
Articles