Application of the Conway–Maxwell–Poisson generalized linear model for analyzing motor vehicle crashes

Lord, Dominique; Guikema, Seth D.; Geedipally, Srinivas Reddy

doi:10.1016/j.aap.2007.12.003

Cited by 202 publications

(136 citation statements)

References 30 publications

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“…In other words, just as NB model, little computation effort is needed to apply the PIG models. Comparatively, recent introduced models such as NB-L model which relies on MCMC chain for parameter estimation may require a few hours simulation before converging (Lord et al, 2008b, Geedipally et al, 2012. Actually, at the end of the paper written by Zou et al (2012b), the potential of applying PIG rather than SI was also addressed mainly for its simplicity.…”

Section: Discussionmentioning

confidence: 99%

“…Firstly, four samples including 80% of the entire data were randomly selected from each dataset for model estimation. Then, the remaining 20% was used to predict crash data based on the obtained regression model (Lord et al, 2008b).…”

Section: Methodsmentioning

confidence: 99%

“…It has been explored by former studies (Lord et al, 2008b, Zou et al, 2012b. Figure 1 shows the distribution of the crash data.…”

Section: Texas Datamentioning

confidence: 99%

“…Each of them has its own characteristics and could provide a better fit compared to the traditional NB model for the corresponding conditions. Such models include, for instance, the Double Poisson (DP) and Conway-Maxwell-Poisson (COMPoisson) for their flexibility of handling both over-dispersion and under-dispersion (Zou et al, 2012a, Lord et al, 2008b; Random-parameter models (Anastasopoulos and Mannering, 2009;Chen and Tarko, 2014) considering the temporal and spatial correlation for longitudinal data; and the Generalized Additive Model (GAM) which extends the GLM and provides more flexible functional forms (Xie and Zhang, 2008).…”

Section: Introductionmentioning

confidence: 99%

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The Poisson inverse Gaussian (PIG) generalized linear regression model for analyzing motor vehicle crash data

Zha

Lord

Zou

2014

Journal of Transportation Safety & Security

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This paper documents the application of the Poisson Inverse Gaussian (PIG) regression model for modeling motor vehicle crash data. The PIG distribution, which mixes the Poisson distribution and Inverse Gaussian distribution, has the potential for modeling highly dispersed count data due to the flexibility of Inverse Gaussian distribution. The objectives of this paper were to evaluate the application of PIG regression model for analyzing motor vehicle crash data and compare the results with Negative binomial (NB) model, especially when varying dispersion parameter is introduced. To accomplish the objectives, both NB and PIG models were developed with fixed and varying dispersion parameters and compared using two datasets. The Texas undivided rural highway segments dataset includes five years of crash data, while the divided highway segments Washington dataset includes four years. The results of this study show that PIG models perform better than the NB models in terms of goodness-of-fit (GOF) statistics. Moreover, PIG models can perform similarly well in capturing the variance of crash to the NB models. Lastly, PIG models demonstrate almost the same prediction performance compared to NB models. Considering the simple form of PIG model and its easiness of applications, PIG model could be used as a potential alternative to the NB model for analyzing crash data. Zha et al.2

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…It has been explored by former studies (Lord et al, 2008b, Zou et al, 2012b. Figure 1 shows the distribution of the crash data.…”

Section: Texas Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Poisson inverse Gaussian (PIG) generalized linear regression model for analyzing motor vehicle crash data

Zha

Lord

Zou

2014

Journal of Transportation Safety & Security

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“…It should be noted that parameter estimation for the dual-link GLM is complex and difficult. To make all the models in this paper comparable, this paper used the single-link COM-Poisson GLM framework (Lord et al, 2008a). The link function is given as:…”

Section: Conway-maxwell-poisson Modelmentioning

confidence: 99%

Evaluating the double Poisson generalized linear model

Zou

Geedipally

Lord

2013

Accident Analysis & Prevention

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Are demographic correlates of white‐faced capuchin monkey (Cebus capucinus) “Gargle and Twargle” vocalization rates consistent with the infanticide risk assessment hypothesis?

Duchesneau

Edelberg

Perry

2021

American J Primatol

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Zahavi's “Bond Testing Hypothesis” states that irritating stimuli are used to elicit honest information from social partners regarding their attitudes towards the relationship. Two elements of the Cebus capucinus vocal repertoire, the “gargle” and “twargle,” have been hypothesized to serve such a bond‐testing function. The greatest threat to C. capucinus infant survival, and to adult female reproductive success, is infanticide perpetrated by alpha males. Thus, we predicted that infants (<8 months), pregnant females and females with infants would gargle/twargle at higher rates than the rest of the population, directing these vocalizations primarily to the alpha male. Over 16 years, researchers collected data via focal follows in 11 habituated groups of wild capuchins in Lomas Barbudal, Costa Rica. We found some support for our hypothesis. Infants and females with infants (<8 months) vocalized at higher rates than the rest of the population. Pregnant females did not vocalize at relatively high rates. Infants (age 8–23 months) were the only target group that vocalized more when the alpha male was not their father. Monkeys gargled and twargled most frequently towards the alpha male, who is both the perpetrator of infanticide and the most effective protector against potentially infanticidal males.

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Application of the Conway–Maxwell–Poisson generalized linear model for analyzing motor vehicle crashes

Cited by 202 publications

References 30 publications

The Poisson inverse Gaussian (PIG) generalized linear regression model for analyzing motor vehicle crash data

The Poisson inverse Gaussian (PIG) generalized linear regression model for analyzing motor vehicle crash data

Evaluating the double Poisson generalized linear model

Are demographic correlates of white‐faced capuchin monkey (Cebus capucinus) “Gargle and Twargle” vocalization rates consistent with the infanticide risk assessment hypothesis?

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