Open AccessAn Optimization of the Autoregressive Model Using the Grid Search Method
Author(s) -
Imam Tahyudin,
Hidetaka Nambo,
Yoshitaka Goto
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.2.12739
Subject(s) - autoregressive model , star model , nonlinear autoregressive exogenous model , estimator , setar , grid , computer science , mathematical optimization , mathematics , autoregressive integrated moving average , statistics , time series , geometry
The purpose of this study is to find the parameters that can produce the best value on the model Autoregressive (AR). The parameter evaluation method used is the Maximum Likelihood Estimator (MLE) and using Grid Search optimization methods. The experimental data used in this study was a sunspot dataset. Based on our analysis, the best Autoregressive model was a 3rd order AR model.