Limiting distributions for explosive PAR(1) time series with strongly mixing innovation
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 num...
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Sprache: | eng |
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Zusammenfassung: | 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 \textgreater{} 0 and such that P r=1 |a r |
\textgreater{} 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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DOI: | 10.48550/arxiv.1501.02151 |