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Structural changes estimation for strongly-dependent processes

Li Song 1 Pascal Bondon 1
1 Division Signaux - L2S
L2S - Laboratoire des signaux et systèmes : 1289
Abstract : In this paper, we consider the problem of estimating multiple structural breaks in a long-memory FARIMA time series. 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 a genetic algorithm is implemented for its optimization. Monte Carlo simulation results show the effectiveness of this criterion and an application to the Nile River data is considered.
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Contributor : Pascal Bondon <>
Submitted on : Friday, January 10, 2014 - 10:11:43 AM
Last modification on : Wednesday, April 8, 2020 - 3:35:00 PM




Li Song, Pascal Bondon. Structural changes estimation for strongly-dependent processes. Journal of Statistical Computation and Simulation, Taylor & Francis, 2013, 83 (10), pp.1783-1806. ⟨10.1080/00949655.2011.653643⟩. ⟨hal-00926709⟩



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