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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