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On fitting of non-stationary autoregressive models in time series analysis
T Ozaki,Howell Tong +1 more
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The article was published on 1975-01-01 and is currently open access. It has received 29 citations till now. The article focuses on the topics: Autoregressive integrated moving average & SETAR.read more
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Journal ArticleDOI
Threshold Autoregression, Limit Cycles and Cyclical Data
Howell Tong,K. S. Lim +1 more
Book ChapterDOI
On the Likelihood of a Time Series Model
TL;DR: By asking the log likelihood of a model to be an unbiased estimate of the expectedlog likelihood of the model, a reasonable definition of the likelihood is obtained and this allows us to develop a systematic approach to parametric time series modelling.
Book ChapterDOI
Locally Stationary Processes
TL;DR: An overview over locally stationary processes with special emphasis on linear processes where a more general theory is possible and the relevance of empirical spectral processes for locally stationary time series is discussed.
Journal ArticleDOI
Estimation of the arrival times of seismic waves by multivariate time series model
TL;DR: In this paper, a computationally efficient procedure was developed for the fitting of many multivariate locally stationary autoregressive models and a method of evaluating the posterior distribution of the change point of the AR model is also presented, in particular useful for the estimation of the S wave of a microearthquake.
Book ChapterDOI
Modern development of statistical methods
TL;DR: In this paper, the authors discuss the use of the minimum akaike information criterion estimation (MAICE) procedure and its conceptual generalization, the entropy maximization principle, in relation to the problem of stochastic system identification.