On stability Conditions of Pareto Autoregressive model
Main Article Content
Abstract
This paper concerned with studding a stability conditions of the proposed non-linear autoregressive time series model Known as Pareto Autoregressive model, acronym is defined by Pareto . A dynamical method Known as local linearization approximation method was used to obtain the stability condition of a non-zero singular point of Pareto model. In addition, we obtain the orbital stability condition of a limit cycle in terms of model parameters when the Pareto possesses a limit cycle with period .
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
Tikrit Journal of Pure Science is licensed under the Creative Commons Attribution 4.0 International License, which allows users to copy, create extracts, abstracts, and new works from the article, alter and revise the article, and make commercial use of the article (including reuse and/or resale of the article by commercial entities), provided the user gives appropriate credit (with a link to the formal publication through the relevant DOI), provides a link to the license, indicates if changes were made, and the licensor is not represented as endorsing the use made of the work. The authors hold the copyright for their published work on the Tikrit J. Pure Sci. website, while Tikrit J. Pure Sci. is responsible for appreciate citation of their work, which is released under CC-BY-4.0, enabling the unrestricted use, distribution, and reproduction of an article in any medium, provided that the original work is properly cited.
References
[1] Tong, H.," Nonlinear Time Series. A Dynamical System Approach", Oxford University Press, New York, 1990
[2] Ozaki, T, "The Statistical Analysis of Perturbed Limit Cycle Processes Using Nonlinear Time Series Models", Journal of Time Series Analysis, Vol.3, N0.1, PP (29-41), 1982
[3] Ozaki, T., "Nonlinear Time Series Models and Dynamical Systems", Handbook of Statistics, Vol. 5, Hannan, E. J. and Krishnailah, P.R. and Rao, M. M., Elsevier Science Publishers R V., PP (25- 83), 1985.
[4] Mohammad A.A., Salim A.J, ''Stability of Logistic Autoregressive Model '', Qatar university of Science journal, Vol (27), PP (17-28), 2007.
[5] Mohammad, A. A., Gannam, A. K., "Stability of Cauchy autoregressive model", Zanco journal of Pure and Applied Sci. – Sallahaddin University – Hawler (special Issue), 2010.
[6] Salim A. J., Esmaeel k., Jasim H. T., ''A study of the stability of an amplitude-dependent exponential autoregressive model with application", Iraqi Journal of Statistical Science, The Fourth Scientific Conference of the College of Computer Science & Mathematics pp (52-62),2011.
[7] Salim, A.J., Youns, A. S.," A Study of the Stability of a Non-Linear Autoregressive Models", Australian J. Basic Appl. Sci. 6 (13), pp (159–166), 2012. [8] Salim, A. G. J., Abdullah, A. S. Y., " Studying the Stability of a Non-linear Autoregressive Model (Polynomial with Hyperbolic Cosine Function)", AL-Rafidain Journal of Computer Sciences and Mathematics, 11(1), pp (81-91), 2014.
[9] Mohammad A. A., Ghaffar M. K., "A study on stability of conditional variance for GARCH models with application", Tikrit journal of pure science, (4) 21,2016.
[10] Mohammad, A. A. and Mudhir, A. A.,"Dynamical approach in studying stability condition of exponential (GARCH) model ", journal of king saud university-science, issue 32, pp(272-278),2020.
[11] NORMANL SOHNSONM. “continuous univariate distributions”, university of North Carolina, second Edition, Vol (1), pp (573-620), 1995.
[12] Namah, M.W., “Estimating parameters Gumbel Pareto distribution”, DIYALA JOURNAL FOR PURE SCIENCES, 14(2), pp(53-60),2018.
[13] Ozaki, T.," Non-linear time series models for non-linear random vibrations", Journal of Applied Probability, 17(1), pp (84-93), 1980.
[14] Haggan, V., & Ozaki, T., "Modelling nonlinear random vibrations using an amplitude-dependent autoregressive time series model", Biometrika, 68(1), pp (189-196), 1981.