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November 1996 Parameter estimation for moving averages with positive innovations
Paul D. Feigin, Marie F. Kratz, Sidney I. Resnick
Ann. Appl. Probab. 6(4): 1157-1190 (November 1996). DOI: 10.1214/aoap/1035463327

Abstract

This paper continues the study of time series models generated by nonnegative innovations which was begun by Feigin and Resnick. We concentrate on moving average processes. Estimators for moving average coefficients are proposed and consistency and asymptotic distributions established for the case of an order-one moving average assuming either the right or the left tail of the innovation distribution is regularly varying. The rate of convergence can be superior to that of the Yule-Walker or maximum likelihood estimators.

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Paul D. Feigin. Marie F. Kratz. Sidney I. Resnick. "Parameter estimation for moving averages with positive innovations." Ann. Appl. Probab. 6 (4) 1157 - 1190, November 1996. https://doi.org/10.1214/aoap/1035463327

Information

Published: November 1996
First available in Project Euclid: 24 October 2002

zbMATH: 0881.62093
MathSciNet: MR1422981
Digital Object Identifier: 10.1214/aoap/1035463327

Subjects:
Primary: 26F10 , 60B10 , 60E20 , 60F05 , 60G55 , 62M10

Keywords: autoregressive processes , consistency , linear programming , moving average processes , Poisson processes , time series analysis , weak convergence

Rights: Copyright © 1996 Institute of Mathematical Statistics

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Vol.6 • No. 4 • November 1996
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