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- W2121206989 abstract "ABSTRACT: The paper develops a linear regression model approach that can be applied to crash data to predict vehicle crashes. The proposed approach involves novice data aggregation to satisfy linear regression assumptions; namely error structure normality and homoscedasticity. The proposed approach is tested and validated using data from 186 access road sections in the state of Virginia. The approach is demonstrated to produce crash predictions consistent with traditional negative binomial and zero inflated negative binomial general linear models. It should be noted however that further testing of the approach on other crash datasets is required to further validate the approach." @default.
- W2121206989 created "2016-06-24" @default.
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- W2121206989 date "2008-11-01" @default.
- W2121206989 modified "2023-09-26" @default.
- W2121206989 title "Linear regression crash prediction models: Issues and proposed solutions" @default.
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- W2121206989 doi "https://doi.org/10.1201/9780203881200-29" @default.
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