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Alternating projections and interpolation of stationary processes

Part of: Stochastic processes Inference from stochastic processes

Published online by Cambridge University Press:  14 July 2016

Mohsen Pourahmadi
Mohsen Pourahmadi*
Affiliation:
Northern Illinois University
*
∗ Postal address: Department of Mathematical Sciences, Northern Illinois University, DeKalb, IL 60115, USA.
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Abstract

By using the alternating projection theorem of J. von Neumann, we obtain explicit formulae for the best linear interpolator and interpolation error of missing values of a stationary process. These are expressed in terms of multistep predictors and autoregressive parameters of the process. The key idea is to approximate the future by a finite-dimensional space.

Keywords

MISSING VALUESPREDICTION AND INTERPOLATION

MSC classification

Primary: 60G25: Prediction theory
Secondary: 62M10: Time series, auto-correlation, regression, etc.
Type
Research Papers
Information
Journal of Applied Probability , Volume 29 , Issue 4 , December 1992 , pp. 921 - 931
Copyright
Copyright © Applied Probability Trust 1992 

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Footnotes

Research supported by AFOSR-88–0284.

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