A cubic regression model to measure the impact of accidents on the number of incidences in the State of Kuwait
DOI:
https://doi.org/10.21533/pen.v9.i4.927Abstract
The regression analysis theories play a crucial part in safety traffic applications. A cubic regression model was specified in this article to fit the annual traffic incidents in Kuwait during the period 2002-2017 based on annual traffic in Kuwait. Estimation results using the least square estimation and the goodness of fit using the sample autocorrelation function are used to demonstrate the appropriateness of the estimated cubic regression model. As a result, the cubic regression model is supported using the residual analysis through the sample ACF, the sample partial ACF, and the normal probability plot NPP figures of the residuals W(n).
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