DocumentCode
3541760
Title
A selection criterion for piecewise stationary long-memory models
Author
Song, Li ; Bondon, Pascal
Author_Institution
Univ. Paris-Sud, Gif-sur-Yvette, France
fYear
2012
fDate
5-8 Aug. 2012
Firstpage
908
Lastpage
911
Abstract
This article considers the problem of estimating multiple structural breaks in a long-memory FARIMA signal. The number of break points as well as their locations, the orders and the parameters of each regime are assumed to be unknown. A selection criterion based on the minimum description length (MDL) principle is proposed and is compared favorably with two existing criteria by means of Monte Carlo simulations.
Keywords
Monte Carlo methods; autoregressive moving average processes; signal processing; Monte Carlo simulations; break points; fractional autoregressive integrated moving average processes; long memory FARIMA signal; minimum description length principle; piecewise stationary long memory models; selection criterion; structural breaks; Biological system modeling; Data models; Estimation; Fitting; Monte Carlo methods; Time series analysis; Vectors; Minimum description length principle; long-memory; non-stationarity;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing Workshop (SSP), 2012 IEEE
Conference_Location
Ann Arbor, MI
ISSN
pending
Print_ISBN
978-1-4673-0182-4
Electronic_ISBN
pending
Type
conf
DOI
10.1109/SSP.2012.6319856
Filename
6319856
Link To Document