Using Time Series Models to Predict the Number of Kidney Patients in Diyala Governorate

Authors

  • Baydaa I. Abdulwahhab
  • Eyas M. Akram

DOI:

https://doi.org/10.55562/jrucs.v56i1.17

Keywords:

Time series, ARIMA model, kidney diseases, autocorrelation, Box- Jenkins models, forecasting

Abstract

 The increase in the number of patients around the world and what this phenomenon causes in terms of human and material losses and the subsequent social and psychological effects that include all segments of society is the main motive and the main goal that directed us for the purpose of conducting this research for this phenomenon and making predictions about it، and the issue of time series is one of the important topics that It deals with the behavior of phenomena and their interpretation over certain time periods، and the importance of time series analysis lies in obtaining an accurate description of the series and defining an appropriate model for prediction and using the results for future planning purposes. In Diyala Governorate for the coming periods so that those in charge can identify the expected numbers in the future to take the necessary precautions to confront this phenomenon and develop ways to address it. On the practical side، the methods mentioned in the theoretical side were applied to a sample of people with kidney disease in the first series، as well as a sample of the artificial  kidney (people with kidney failure) for the second series، with a volume of (55) for the period from December 2018 to July 2022، and they are not They are stable according to the values of the autocorrelation coefficients، and both series have a general trend. The first difference was taken in both cases to make them stable and obtain predictions close to the true values. The time square variable in the quadratic model of the series of kidney diseases had an inverse effect because its sign was negative، as the estimated parameter reached (0.644). ) but its effect is slight due to the decrease in the value of the estimated parameter، and that the ARIMA (3،1،3) model is the only significant and best for a series of kidney diseases that can be relied upon in making predictions of the number of kidney patients، and the same is the case، the best model for the industrial kidney series is the ARIMA model (2، 1،2) among the rest of the other intangible models can be relied upon in making predictions about the numbers of the Industrial kidney in Diyala Governorate

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Published

2025-01-05

How to Cite

Using Time Series Models to Predict the Number of Kidney Patients in Diyala Governorate . (2025). Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), 56(1), 183-201. https://doi.org/10.55562/jrucs.v56i1.17