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March, 1994 Identification of Nonlinear Time Series from First Order Cumulative Characteristics
Ian W. McKeague, Mei-Jie Zhang
Ann. Statist. 22(1): 495-514 (March, 1994). DOI: 10.1214/aos/1176325381

Abstract

A new approach to the problem of identifying a nonlinear time series model is considered. We argue that cumulative lagged conditional mean and variance functions are the appropriate "signatures" of a nonlinear time series for the purpose of model identification, being analogous to cumulative distribution functions or cumulative hazard functions in iid models. We introduce estimators of the cumulative lagged conditional mean and variance functions and study their asymptotic properties. A goodness-of-fit test for parametric time series models is also developed.

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Ian W. McKeague. Mei-Jie Zhang. "Identification of Nonlinear Time Series from First Order Cumulative Characteristics." Ann. Statist. 22 (1) 495 - 514, March, 1994. https://doi.org/10.1214/aos/1176325381

Information

Published: March, 1994
First available in Project Euclid: 11 April 2007

zbMATH: 0797.62073
MathSciNet: MR1272096
Digital Object Identifier: 10.1214/aos/1176325381

Subjects:
Primary: 62M10
Secondary: 62G02, 62G07, 62M02

Rights: Copyright © 1994 Institute of Mathematical Statistics

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Vol.22 • No. 1 • March, 1994
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