Building a Statistical Model to Forecast Traffic Accidents for Death and Injuries by Using Bivariate Time Series Analysis
In our study, multivariate time series were used that included two variables, namely, the death and injury rates from car accidents in Erbil City Iraq. The data for the two series were collected monthly from January 2015 to December 2020, so there are 72 units in each series. The most important fin...
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| Format: | Article |
| Language: | Arabic |
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Salahaddin University-Erbil
2024-02-01
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| Series: | Zanco Journal of Humanity Sciences |
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| Online Access: | https://zancojournal.su.edu.krd/index.php/JAHS/article/view/1442 |
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| author | Nozad Hussein Mahmood Dler Hussen Kadir Obaid Mahmud Mohsin Alzawbaee |
| author_facet | Nozad Hussein Mahmood Dler Hussen Kadir Obaid Mahmud Mohsin Alzawbaee |
| author_sort | Nozad Hussein Mahmood |
| collection | DOAJ |
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In our study, multivariate time series were used that included two variables, namely, the death and injury rates from car accidents in Erbil City Iraq. The data for the two series were collected monthly from January 2015 to December 2020, so there are 72 units in each series. The most important finding is that the time series is stationary, and the appropriate model to represent the phenomenon studied is VARMA (1,0). A statistical model was adopted to forecast accidents resulting in death and injuries for 2024, and it was found to be appropriate. Furthermore, we use R-programing and STATA version 17 to analyze our data. As a result, the study suggested that the Iraqi Kurdistan Traffic Department could use the model developed to forecast the phenomenon's future trends.
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| format | Article |
| id | doaj-art-86d0dfc2acae49ecbc75fdbbf7664e60 |
| institution | DOAJ |
| issn | 2412-396X |
| language | Arabic |
| publishDate | 2024-02-01 |
| publisher | Salahaddin University-Erbil |
| record_format | Article |
| series | Zanco Journal of Humanity Sciences |
| spelling | doaj-art-86d0dfc2acae49ecbc75fdbbf7664e602025-08-20T03:06:49ZaraSalahaddin University-ErbilZanco Journal of Humanity Sciences2412-396X2024-02-0128110.21271/zjhs.28.1.18Building a Statistical Model to Forecast Traffic Accidents for Death and Injuries by Using Bivariate Time Series AnalysisNozad Hussein Mahmood 0Dler Hussen Kadir 1Obaid Mahmud Mohsin Alzawbaee 2Department of Business Administration, Cihan University Sulaimaniya, 46001, Kurdistan region, IraqDepartment of Statistics and Informatics, College of Administration and Economics, Salahaddin University-Erbil Kurdistan Region, Iraq Department of Business Administration, Cihan University-Erbil, Kurdistan Region, IraqDepartment of Business Administration, Cihan University Sulaimaniya, 46001, Kurdistan region, Iraq In our study, multivariate time series were used that included two variables, namely, the death and injury rates from car accidents in Erbil City Iraq. The data for the two series were collected monthly from January 2015 to December 2020, so there are 72 units in each series. The most important finding is that the time series is stationary, and the appropriate model to represent the phenomenon studied is VARMA (1,0). A statistical model was adopted to forecast accidents resulting in death and injuries for 2024, and it was found to be appropriate. Furthermore, we use R-programing and STATA version 17 to analyze our data. As a result, the study suggested that the Iraqi Kurdistan Traffic Department could use the model developed to forecast the phenomenon's future trends. https://zancojournal.su.edu.krd/index.php/JAHS/article/view/1442Multivariate time series, VARMA (p, q), Forecasting, Traffic Accident. |
| spellingShingle | Nozad Hussein Mahmood Dler Hussen Kadir Obaid Mahmud Mohsin Alzawbaee Building a Statistical Model to Forecast Traffic Accidents for Death and Injuries by Using Bivariate Time Series Analysis Zanco Journal of Humanity Sciences Multivariate time series, VARMA (p, q), Forecasting, Traffic Accident. |
| title | Building a Statistical Model to Forecast Traffic Accidents for Death and Injuries by Using Bivariate Time Series Analysis |
| title_full | Building a Statistical Model to Forecast Traffic Accidents for Death and Injuries by Using Bivariate Time Series Analysis |
| title_fullStr | Building a Statistical Model to Forecast Traffic Accidents for Death and Injuries by Using Bivariate Time Series Analysis |
| title_full_unstemmed | Building a Statistical Model to Forecast Traffic Accidents for Death and Injuries by Using Bivariate Time Series Analysis |
| title_short | Building a Statistical Model to Forecast Traffic Accidents for Death and Injuries by Using Bivariate Time Series Analysis |
| title_sort | building a statistical model to forecast traffic accidents for death and injuries by using bivariate time series analysis |
| topic | Multivariate time series, VARMA (p, q), Forecasting, Traffic Accident. |
| url | https://zancojournal.su.edu.krd/index.php/JAHS/article/view/1442 |
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