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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| Main Authors: | , , |
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| Format: | Article |
| Language: | Arabic |
| Published: |
Salahaddin University-Erbil
2024-02-01
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| Series: | Zanco Journal of Humanity Sciences |
| Subjects: | |
| Online Access: | https://zancojournal.su.edu.krd/index.php/JAHS/article/view/1442 |
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| Summary: | 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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| ISSN: | 2412-396X |