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Chapitre D'ouvrage Année : 2015

Limiting distributions for explosive PAR(1) time series with strongly mixing innovation

Résumé

This work deals with the limiting distribution of the least squares estimators of the coefficients a r of an explosive periodic autoregressive of order 1 (PAR(1)) time series X r = a r X r−1 +u r when the innovation {u k } is strongly mixing. More precisely {a r } is a periodic sequence of real numbers with period P > 0 and such that P r=1 |a r | > 1. The time series {u r } is periodically distributed with the same period P and satisfies the strong mixing property, so the random variables u r can be correlated.
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Dates et versions

hal-01101744 , version 1 (09-01-2015)

Identifiants

Citer

Dominique Dehay. Limiting distributions for explosive PAR(1) time series with strongly mixing innovation. Fakher Chaari; Jacek Leskow; Antonio Napolitano; Radoslaw Zimroz; Agnieszka Wylomanska; Anna Dudek. Cyclostationarity: Theory and Methods - II. Contributions to the 7th Workshop on Cyclostationary Systems And Their Applications, Grodek, Poland, 2014, 3, Springer, pp.105-129, 2015, Applied Condition Monitoring, 978-3-319-16329-1. ⟨10.1007/978-3-319-16330-7_6⟩. ⟨hal-01101744⟩
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