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Conference papers
A robust estimation approach for fitting a PARMA model to real data
Abstract : This paper proposes an estimation approach of the Whittle estimator to fit periodic autoregressive moving average (PARMA) models when the process is contaminated with additive outliers and/or has heavy-tailed noise. It is derived by replacing the ordinary Fourier transform with the non-linear M-regression estimator in the harmonic regression equation that leads to the classical periodogram. A Monte Carlo experiment is conducted to study the finite sample size of the proposed estimator under the scenarios of contaminated and non-contaminated series. The proposed estimation method is applied to fit a PARMA model to the sulfur dioxide (SO2) daily average pollutant concentrations in the city of Vitória (ES), Brazil.
https://hal-agroparistech.archives-ouvertes.fr/hal-01560258
Contributor : Armelle Sielinou Connect in order to contact the contributor
Submitted on : Tuesday, July 11, 2017 - 2:16:30 PM
Last modification on : Wednesday, November 17, 2021 - 3:02:26 AM
Contributor : Armelle Sielinou Connect in order to contact the contributor
Submitted on : Tuesday, July 11, 2017 - 2:16:30 PM
Last modification on : Wednesday, November 17, 2021 - 3:02:26 AM