Linear approximations to some non-linear AR(1) processes
Kybernetika (2000)
- Volume: 36, Issue: 4, page [389]-399
- ISSN: 0023-5954
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topAnděl, Jiří. "Linear approximations to some non-linear AR(1) processes." Kybernetika 36.4 (2000): [389]-399. <http://eudml.org/doc/33491>.
@article{Anděl2000,
abstract = {Some methods for approximating non-linear AR(1) processes by classical linear AR(1) models are proposed. The quality of approximation is studied in special non-linear AR(1) models by means of comparisons of quality of extrapolation and interpolation in the original models and in their approximations. It is assumed that the white noise has either rectangular or exponential distribution.},
author = {Anděl, Jiří},
journal = {Kybernetika},
language = {eng},
number = {4},
pages = {[389]-399},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Linear approximations to some non-linear AR(1) processes},
url = {http://eudml.org/doc/33491},
volume = {36},
year = {2000},
}
TY - JOUR
AU - Anděl, Jiří
TI - Linear approximations to some non-linear AR(1) processes
JO - Kybernetika
PY - 2000
PB - Institute of Information Theory and Automation AS CR
VL - 36
IS - 4
SP - [389]
EP - 399
AB - Some methods for approximating non-linear AR(1) processes by classical linear AR(1) models are proposed. The quality of approximation is studied in special non-linear AR(1) models by means of comparisons of quality of extrapolation and interpolation in the original models and in their approximations. It is assumed that the white noise has either rectangular or exponential distribution.
LA - eng
UR - http://eudml.org/doc/33491
ER -
References
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- Tong H., Non-linear Time Series, Clarendon Press, Oxford 1990 Zbl0835.62076
- Young P., Time variable and state dependent modelling of non-stationary and nonlinear time series, In: Developments in Time Series Analysis (T. Subba Rao, ed.), Chapman and Hall, London 1993, pp. 374–413 (1993) Zbl0880.62100
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