Univariate nonlinear time series models
AbstractIn this paper developments in the analysis of univariate nonlinear time series are considered. First a number of commonly used nonlinear models are presented. The next section is devoted to methods of testing linearity, which is an important part of nonlinear model building. Techniques of modelling nonlinear series within a predetermined family of models are discussed thereafter. Forecasting with nonlinear models also has its own section. A brief set of final remarks closes the chapter.
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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 593.
Length: 37 pages
Date of creation: 29 Mar 2005
Date of revision:
Publication status: Published in Palgrave Handbook of Econometrics, Volume 1: Econometrics, Patterson, Kerry, Mills, Terence C. (eds.), 2006, chapter 10, pages 396-424, Palgrave Macmillan.
Note: This paper has been prepared for Kerry Patterson and Terence C. Mills (eds.), Palgrave Handbook of Econometrics, Volume 1: Econometric Theory, Palgrave Macmillan.
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Hidden Markov model; linearity test; neural network; nonlinear model building; threshold autoregressive model; smooth transition autoregressive model;
Find related papers by JEL classification:
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-04-03 (All new papers)
- NEP-ECM-2005-04-03 (Econometrics)
- NEP-ETS-2005-04-03 (Econometric Time Series)
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