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The Representation and Decomposition of Integrated Stationary Time Series

Part of: Inference from stochastic processes

Published online by Cambridge University Press:  01 July 2016

Zhao-Guo Chen  and
Oliver D. Anderson
Zhao-Guo Chen*
Affiliation:
Statistics Canada
Oliver D. Anderson*
Affiliation:
University of Western Ontario
*
* Postal address: Time Series Research and Analysis Center, R. H. Coats Building, Statistics Canada, Ottawa, Ontario, Canada K1A 0T6.
** Postal address: Department of Statistical and Actuarial Sciences, Room 262 Western Science Centre, University of Western Ontario, London, Ontario, Canada N6A 5B7.
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Abstract

Learning from Matheron's representation (1973), and using the increment vector (PIV) methodology introduced by Cressie (1988) and developed by Chen and Anderson (1994), this paper presents a theory for the representation and decomposition of integrated stationary time series and gives some applications.

Keywords

DEGREE OF DIFFERENCINGDIFFERENCE EQUATIONSFORECASTINGFUNDAMENTALGENERALISEDAND PRIMARY INCREMENT VECTORSId AND Īd-SERIESINTRINSIC RANDOM FUNCTION AND ITS REPRESENTATIONOVERINTEGRATED MODELSRATE OF DIVERGENCEWOLD DECOMPOSITION

MSC classification

Primary: 62M10: Time series, auto-correlation, regression, etc.
Type
General Applied Probability
Information
Advances in Applied Probability , Volume 26 , Issue 3 , September 1994 , pp. 799 - 819
Copyright
Copyright © Applied Probability Trust 1994 

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