DocumentCode :
1657095
Title :
Structural breaks estimation for long memory signals
Author :
Song, Li ; Bondon, Pascal
Author_Institution :
CNRS, Univ. Paris-Sud, Gif-sur-Yvette, France
fYear :
2009
Firstpage :
237
Lastpage :
240
Abstract :
We consider the problem of estimating the structural breaks in a long memory FARIMA process. The number m of break points as well as their locations, the order (p, d, q) and the parameters of each regime are assumed to be unknown. To estimate the unknown parameters, we propose two criteria based on the minimum description length (MDL) principle of Rissanen, namely a direct extension of MDL and an improved MDL criterion embedded with Bayes information criterion (BIC). A genetic algorithm is implemented to optimize these two criteria. Monte Carlo simulation results show that both criteria perform well for estimating the break points number and their locations. The direct extension of MDL tends to over-estimate the regimes model order which is not the case of the improved MDL criterion.
Keywords :
Bayes methods; Monte Carlo methods; estimation theory; genetic algorithms; signal processing; Bayes information criterion; Monte Carlo simulation; Rissanen principle; genetic algorithm; long memory FARIMA process; long memory signals; minimum description length; structural break estimation; Bonding; Difference equations; Electronic equipment testing; Genetic algorithms; Hydrology; Meteorology; Parameter estimation; Signal processing; Statistical analysis; Yttrium; Long memory; MDL; Piecewise FARIMA model; Structural breaks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
Conference_Location :
Cardiff
Print_ISBN :
978-1-4244-2709-3
Electronic_ISBN :
978-1-4244-2711-6
Type :
conf
DOI :
10.1109/SSP.2009.5278596
Filename :
5278596
Link To Document :
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