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February, 1995 Prediction and Non-Gaussian Autoregressive Stationary Sequences
Murray Rosenblatt
Ann. Appl. Probab. 5(1): 239-247 (February, 1995). DOI: 10.1214/aoap/1177004838

Abstract

The object of this paper is to show that under certain auxiliary assumptions a stationary autoregressive sequence has a best predictor in mean square that is linear if and only if the sequence is minimum phase or is Gaussian when all moments are finite.

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Murray Rosenblatt. "Prediction and Non-Gaussian Autoregressive Stationary Sequences." Ann. Appl. Probab. 5 (1) 239 - 247, February, 1995. https://doi.org/10.1214/aoap/1177004838

Information

Published: February, 1995
First available in Project Euclid: 19 April 2007

zbMATH: 0828.62084
MathSciNet: MR1325051
Digital Object Identifier: 10.1214/aoap/1177004838

Subjects:
Primary: 60G25
Secondary: 10J10 , 60G10 , 62M20

Keywords: Autoregressive sequence , non-Gaussian , nonlinear prediction , non-minimum phase

Rights: Copyright © 1995 Institute of Mathematical Statistics

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Vol.5 • No. 1 • February, 1995
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