Open AccessModeling Time Series for Prediction of Thalassemia in Nineveh Governorate
Author(s) -
Shaymaa Riyadh Thanoon
Publication year - 2021
Publication title -
mağallaẗ sāmarrāʾ al-ʿulūm al-ṣirfaẗ wa-al-taṭbīqiyyaẗ
Language(s) - English
Resource type - Journals
eISSN - 2789-6838
pISSN - 2663-7405
DOI - 10.54153/sjpas.2020.v2i3.30
Subject(s) - autoregressive integrated moving average , box–jenkins , series (stratigraphy) , time series , statistics , moving average , autoregressive–moving average model , mathematics , thalassemia , econometrics , computer science , medicine , autoregressive model , biology , paleontology
The aim of this research is to analyze the time series of Thalassemia cancer cases by making assumptions on the number of cases to formulate the problem to find the best model for predicting the number of patients in Nineveh governorate using (Box and Jenkins) method of analysis based on the monthly data provided by Al Salam Hospital in Nineveh for the period (2014-2018). The results of the analysis showed that the appropriate model of analysis is the Auto-Regressive Integrated Moving Average (ARIMA) (2,1,0) and based on this model the number of people with this disease was predicted for the next two years where the results showed values consistent with the original values which indicates the good quality of the model.