Abstract
Researchers have great interest in studying the black box models this thesis has been focused in the study one of the black box models , a ARMAX model which is one of the important models and can be accessed through a number of special cases which models (AR , MA , ARMA, ARX) , which combines method of the time series that depend on historical data and and regression method as explanatory variables addition to that past errors , ARMAX model importance has appeared in many areas of application that direct contact with our daily lives , it consists of constructing ARMAX model several traditional stages of the process , a identification As it was used Final prediction error (FPE) , Akaiki Information Criterion (AIC) and estimate As it was used Recursive least square with Forgetting Factor (RLS – F) and Recursive pseudolinear regression method (RPLR) which come in the first place and (RLS – F) which come in the second place and finally come prediction for (30) value of the daily maximum temperature depending on the daily wind speed .
DOI
10.33095/jeas.v22i88.567
Subject Area
Statistical
First Page
420
Last Page
430
Recommended Citation
Mohammed AL-Mohana, F. A., & Fakhri, M. A. (2016). Predict the Values of the Time Series Using the (ARMAX) Model with Practical Application. Journal of Economics and Administrative Sciences, 22(88), 420-430. https://doi.org/10.33095/jeas.v22i88.567
