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On geometric ergodicity and prediction in nonnegative non-linear autoregressive processes
Kybernetika, Tome 40 (2004) no. 6, pp. 691-702 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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A non-linear AR(1) process is investigated when the associated white noise is positive. A criterion is derived for the geometric ergodicity of the process. Some explicit formulas are derived for one and two steps ahead extrapolation. Influence of parameter estimation on extrapolation is studied.
A non-linear AR(1) process is investigated when the associated white noise is positive. A criterion is derived for the geometric ergodicity of the process. Some explicit formulas are derived for one and two steps ahead extrapolation. Influence of parameter estimation on extrapolation is studied.
Classification : 62M10, 62M20
Keywords: geometric ergodicity; non-linear autoregression; least squares extrapolation 
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Zvára, Petr. On geometric ergodicity and prediction in nonnegative non-linear autoregressive processes. Kybernetika, Tome 40 (2004) no. 6, pp. 691-702. http://geodesic.mathdoc.fr/item/KYB_2004_40_6_a3/

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