This paper proposes a non parametric approach for dating structural breaks whose number and dates of occurrence are a priori unknown. In particular, the case of level shifts is considered. For the purpose of locating the break-dates the method exploits, in the framework of least square regression trees, the contiguity property introduced by Fisher for grouping a single real variable. The proposal is applied to the study of the mean water level of Michigan Huron lake also comparing the results to those of the well known procedure recently proposed by Bai and Perron.

Detecting multiple structural breaks in the mean via Atheoretical Regression Trees / Cappelli, Carmela; M., Reale. - STAMPA. - (2005), pp. 131-134. (Intervento presentato al convegno IWSM 2005 20-thInternational Workshop on Statistical Modelling tenutosi a Sidney, Australia nel 10-15 July 2005).

Detecting multiple structural breaks in the mean via Atheoretical Regression Trees

CAPPELLI, CARMELA;
2005

Abstract

This paper proposes a non parametric approach for dating structural breaks whose number and dates of occurrence are a priori unknown. In particular, the case of level shifts is considered. For the purpose of locating the break-dates the method exploits, in the framework of least square regression trees, the contiguity property introduced by Fisher for grouping a single real variable. The proposal is applied to the study of the mean water level of Michigan Huron lake also comparing the results to those of the well known procedure recently proposed by Bai and Perron.
2005
9781741081015
Detecting multiple structural breaks in the mean via Atheoretical Regression Trees / Cappelli, Carmela; M., Reale. - STAMPA. - (2005), pp. 131-134. (Intervento presentato al convegno IWSM 2005 20-thInternational Workshop on Statistical Modelling tenutosi a Sidney, Australia nel 10-15 July 2005).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/371735
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