A new robust estimation method for ARMA models

Author

Chakhchoukh, Yacine ; Panciatici, Patrick ; Bondon, Pascal ; Mili, Lamine

Author_Institution

RTE, DMA, Versailles

fYear

2009

fDate

19-24 April 2009

Firstpage

3321

Lastpage

3324

Abstract

This paper presents a new robust method to estimate the parameters of ARMA models. This method makes use of the autocorrelations estimates based on the ratio of medians together with a robust filter cleaner able to reject a large fraction of outliers, and a Gaussian maximum likelihood estimation which handles missing values. The main advantages of the procedure are its easiness, robustness and fast execution. Its effectiveness is demonstrated on an example of the forecasting of the French daily electricity consumptions.

Keywords

Gaussian processes; autoregressive moving average processes; maximum likelihood estimation; ARMA models; French daily electricity consumptions; Gaussian maximum likelihood estimation; robust estimation method; robust filter cleaner; Autocorrelation; Distribution functions; Electric breakdown; Energy consumption; Filtering; Filters; Maximum likelihood estimation; Parameter estimation; Robustness; Statistics; ARMA models; Robustness; missing values; outliers; time series;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Conference_Location

Taipei

ISSN

1520-6149

Print_ISBN

978-1-4244-2353-8

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2009.4960335

Filename

4960335