The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.
DOI:
https://doi.org/10.33095/jeas.v13i48.1228Keywords:
المقارنة بين طرائق تحديد رتبة انموذج الانحدار الذاتي الطبيعي (باستخدام بيانات مولدّة وبيانات لبعض العناصر المناخية في العراق)Abstract
The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.
Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.
The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.
In the analysis of data there are many suitable models that can be taken for representation in certain groups of data (autocorrelation function ACF, partial autocorrelation function PACF and inverse autocorrelation function IACF).
In this search a comparison was done using generated data (simulation) and practical application, namely, the data of some climate elements in Iraq (sun-shine, temperatures and relative humidity). Where some new results are obtained.
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