Current developments in time series modelling

In this paper a survey is given of some current developments in time series analysis. After a brief discussion of linear models, ARMA models and state–space reprentations, the discussion concentrates on a fairly general class of non-linear models called ‘state-dependent models’ and the applications...

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Bibliographic Details
Published in:Journal of econometrics 1988, Vol.37 (1), p.67-86
Main Author: Priestley, M.B.
Format: Article
Language:English
Subjects:
Estimating techniques
Exact sciences and technology
Inference from stochastic processes
time series analysis
Linear programming
Markov analysis
Mathematical models
Mathematics
Probability and statistics
Sciences and techniques of general use
Simulation
Statistical analysis
Statistics
Time series
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Summary:In this paper a survey is given of some current developments in time series analysis. After a brief discussion of linear models, ARMA models and state–space reprentations, the discussion concentrates on a fairly general class of non-linear models called ‘state-dependent models’ and the applications of these to the problem of identifying general forms of non-linear structure. The effectiveness of the estimation technique is studied by means of numerical examples on simulated data. Towards the end of the paper it is indicated how these ideas may be applied to the study of systems governed by non-linear differential equations.
ISSN:0304-4076
1872-6895
DOI:10.1016/0304-4076(88)90076-0