MODELING NON-LINEAR RANDOM VIBRATIONS USING AN AMPLITUDE-DEPENDENT AUTOREGRESSIVE TIME-SERIES MODEL
成果类型：
Article
署名作者：
HAGGAN, V; OZAKI, T
署名单位：
Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/68.1.189
发表日期：
1981
页码：
189196
关键词：
摘要：
The behavior of nonlinear deterministic vibrations was studied and may typically include such features as jump phenomena and limit cycles. Nonlinear random vibrations in continuous time were also studied previously; these may commonly give rise to the phenomenon of amplitude-dependent frequency. A discrete time series model is introduced, which may have properties similar to those of nonlinear random vibrations. This model is of autoregressive form with amplitude-dependent coefficients and may be estimated using an extension of a method for estimating linear time series models. The model is fitted to the Canadian lynx data and demonstrates that it may be possible to regard the periodic behavior of this series as being generated by some underlying self-exciting mechanism.