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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
Published in: journal Statistics, Volume 20, Issue 4 1989 , pages 615 - 632
Formats available: PDF (English)
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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.
Keywords: Nonlinear processes threshold models bilinear models autoregressive models with random parameters; tests of linearity; stationary distribution
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