On nonlinear models for time series
Author:
Jiri Andel a
| Affiliation: | a Deportment of Statistics, Charles University, Prague 8, Czechoslovakia |
DOI:
10.1080/02331888908802217
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
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Abstract
The paper is a review of nonlinear processes used in time series analysis and presents some new original results about stationary distribution of a nonlinear autoregres-sive process of the first order. The following models are considered: nonlinear autoregessive processes, threshold AR processes, threshold MA processes, bilinear models, auto-regressive models with random parameters including double stochastic models, exponential AR models, generalized threshold models and smooth transition autoregressive models, Some tests for linearity of processes are also presented.
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| Keywords: Nonlinear processes threshold models bilinear models autoregressive models with random parameters; tests of linearity; stationary distribution |
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