The ARMA(p,q) model is estimated when the error is random and has a Laplace distribution by practical rule
DOI:
https://doi.org/10.31272/jae.i142.1041Keywords:
mixed model ARMA (p,q), Laplace Maximum Likelihood Method, Time series .Abstract
This research dealt with one of the types of studies proposed by Box-Jenkins, which is the ARMA (1,1) mixed model. Which affects the handling of timelines, whether they exist or not. It was identified with the indirect model with the non-normal distribution, and the Laplace distribution was one of the members of the masses. It touched on the most important topics targeted by the model, as the parameters of the ARMA model (1,1) were estimated using the MLE method. In the side application, a set of real data was analyzed, which represents a number of new data different according to the months from 2015-2022, and they determine the distribution of the main data and verify the interception of the tree, and in the diagnostic model it was found that the appropriate model is ARMA (1,1) .
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References
- Al-Azzawi, Majid Rashid. (2001) “On some properties of the non-normal ARMA(1,1) mixed model” Doctoral thesis in Statistics, College of administration and Economics, University of Baghdad.
- Sheikhi, Muhammad (2011) “Economic measurement methods, lectures and applications,” professor and researcher at the University of Ouargla, Algeria, first edition, Al-Hamid.
- Al-Badrawi, Ali Yassin (2015), “The effect of the non-normal distribution of random error terms in estimating the parameters of some ARMA-GARCH models with a practical application,” PhD thesis in statistics, College of Administration and Economics, Al-Mustansiriya University.
-ali & Rawa 'Estimate the parameters of the ARMA model when the random error follows a Lindley distribution' Al-Mustansiriya University / College of Administration and Economics.
- Cryer& Kung.(2008)' Time Series Analysis DOI: https://doi.org/10.1007/978-0-387-75959-3
With Applications in R' Second Edition. Library of Congress Control Number
-Daniel, Wayne W. (1990). "Kolmogorov–Smirnov one-sample test". Applied Nonparametric Statistics (2nd ed.). Boston: PWS-Kent. pp. 319–330. ISBN 978-0-534-91976-4.
-Divad $Robert "Time Series Analysis and applaction"Third edition
-Wei. William, W.S.; (1989), “Time-Series Analysis Univariate And
Multivariate Methods "Department of Statistics the fox school of Business and Management templ university. Addison-Wesley Publishing Company Ine.
- Hameed ,Lamyaa. M(2022) 'A proposed conditional method for estimating ARMA(1, 1) model' Department of Statistics, College of Administration and Economic, Baghdad University, Iraq.
-Lavan,M,&Paul,R,(2004)"Unit roots testing to help model building "Handbooks in central banking,No.22,
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