Title of article :
New Optimized Model Identification in Time Series Model and Its Difficulties
Author/Authors :
Zanboori, Ahmad Reza Department of Statistics - Marvdasht Branch - Islamic Azad University , Zare, Karim Department of Statistics - Marvdasht Branch - Islamic Azad University
Abstract :
Model identification is an important and complicated step within
the autoregressive integrated moving average (ARIMA) methodology
framework. This step is especially difficult for integrated series. In
this article first investigate Box-Jenkins methodology and its faults
in detecting model, and hence have discussed the problem of outliers
in time series. By using this optimization method, we will overcome
this problem. The method that used in this paper is better than the
Box-Jenkins in term of optimality time
Keywords :
time series , outliers , box-jenkins , extended sample autocorrelation , function
Journal title :
Astroparticle Physics
