Structural Changes Estimation for Strongly-dependent Processes
نویسندگان
چکیده
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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