Stationary distribution of absolute autoregression

Jiří Anděl; Pavel Ranocha

Kybernetika (2005)

  • Volume: 41, Issue: 6, page [735]-742
  • ISSN: 0023-5954

Abstract

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A procedure for computation of stationary density of the absolute autoregression (AAR) model driven by white noise with symmetrical density is described. This method is used for deriving explicit formulas for stationary distribution and further characteristics of AAR models with given distribution of white noise. The cases of Gaussian, Cauchy, Laplace and discrete rectangular distribution are investigated in detail.

How to cite

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Anděl, Jiří, and Ranocha, Pavel. "Stationary distribution of absolute autoregression." Kybernetika 41.6 (2005): [735]-742. <http://eudml.org/doc/33784>.

@article{Anděl2005,
abstract = {A procedure for computation of stationary density of the absolute autoregression (AAR) model driven by white noise with symmetrical density is described. This method is used for deriving explicit formulas for stationary distribution and further characteristics of AAR models with given distribution of white noise. The cases of Gaussian, Cauchy, Laplace and discrete rectangular distribution are investigated in detail.},
author = {Anděl, Jiří, Ranocha, Pavel},
journal = {Kybernetika},
keywords = {absolute autoregression; stationary distribution; marginal distribution; absolute autoregression; stationary distribution; marginal distribution},
language = {eng},
number = {6},
pages = {[735]-742},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Stationary distribution of absolute autoregression},
url = {http://eudml.org/doc/33784},
volume = {41},
year = {2005},
}

TY - JOUR
AU - Anděl, Jiří
AU - Ranocha, Pavel
TI - Stationary distribution of absolute autoregression
JO - Kybernetika
PY - 2005
PB - Institute of Information Theory and Automation AS CR
VL - 41
IS - 6
SP - [735]
EP - 742
AB - A procedure for computation of stationary density of the absolute autoregression (AAR) model driven by white noise with symmetrical density is described. This method is used for deriving explicit formulas for stationary distribution and further characteristics of AAR models with given distribution of white noise. The cases of Gaussian, Cauchy, Laplace and discrete rectangular distribution are investigated in detail.
LA - eng
KW - absolute autoregression; stationary distribution; marginal distribution; absolute autoregression; stationary distribution; marginal distribution
UR - http://eudml.org/doc/33784
ER -

References

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  1. Anděl J., Dependent random variables with a given marginal distribution, Acta Univ. Carolin. – Math. Phys. 24 (1983), 3–12 (1983) MR0733140
  2. Anděl J., Marginal distributions of autoregressive processes, In: Trans. 9th Prague Conference Inform. Theory, Statist. Dec. Functions, Random Processes. Academia, Praha 1983 Zbl0537.60027MR0757732
  3. Anděl J., Bartoň T., 10.1111/j.1467-9892.1986.tb00481.x, J. Time Ser. Anal. 7 (1986), 1–5 (1986) Zbl0587.60033MR0832348DOI10.1111/j.1467-9892.1986.tb00481.x
  4. Anděl J., Netuka, I., Zvára K., On threshold autoregressive processes, Kybernetika 20 (1984), 89–106 (1984) Zbl0547.62058MR0747062
  5. Chan K. S., Tong H., 10.1007/BF01845999, Probab. Theory Related Fields 73 (1986), 153–159 (1986) MR0849071DOI10.1007/BF01845999
  6. Loges W., 10.1111/j.1467-9892.2004.00339.x, J. Time Ser. Anal. 25 (2004), 103–125 Zbl1051.62080MR2042113DOI10.1111/j.1467-9892.2004.00339.x
  7. Tong H., Non-Linear Time Series, Clarendon Press, Oxford 1990 Zbl0835.62076

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