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
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