Reversed residuals in autoregressive time series analysis
By: Peter A.W. Lewis, and A.J. Lawrence
Contributors: Lawrence, A. J.; Naval Postgraduate School (U.S.). Dept. of Operations Research
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1990
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Number of pages: 12
Subjects: TIME SERIES ANALYSIS; RESIDUALS; STATISTICAL ANALYSIS
Other titles: NPS-55-90-11.
Description: Both linear and nonlinear time series can have directional features, features which indicate that      the series do not maintain identical statistical properties when the direction on the time scale is      reversed. The main purpose of the present paper is to develop the analysis of these features      and to indicate and illustrate how they can be used for the investigation and modelling of linear      or nonlinear autoregressive statistical models. In particular, the aim of the paper is to introduce      the idea of reversed residuals and to develop some of their properties. Particular pairs of      reversed and ordinary residuals are shown to produce partial autocorrelation coefficients:      quadratic types of partial autocorrelation coefficients are introduced to assess dependence      associated with nonlinear models which nevertheless have linear autoregressive (Yule-Walker)      correlation structures. (kr)
Notes: Title from cover.

"NPS-55-90-11."

"April 1990."

AD A222 711.

Includes bibliographical references (p. 11-12).

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