Limit distributions for linear programming time series estimators
We consider stationary autoregressive processes of order p which have positive innovations. We propose consistent parameter estimators based on linear programming. Under conditions, including regular variation of either the left or right tail of the innovations distribution, we prove that the estimators have a limit distribution. The rate of convergence of our estimator is favorable compared with the Yule--Walker estimator under comparable circumstances.
Year of publication: |
1994
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Authors: | Feigin, Paul D. ; Resnick, Sidney I. |
Published in: |
Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 51.1994, 1, p. 135-165
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Publisher: |
Elsevier |
Keywords: | Poisson processes Linear programming Autoregressive processes Parameter estimation Weak convergence Consistency Time series analysis |
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