A latent variable representation of count data models to accommodate spatial and temporal dependence: application to predicting crash frequency at intersections

By Marisol Castro, Rajesh Paleti, Chandra R. Bhat. 2011

180 citations recorded by the source corpus.

Subfields: Safety, Risk, Reliability and Quality, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/2cc0171fff6802cc46377bf1972174f17bc22efe

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In Safety, Risk, Reliability and Quality

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Citations in the corpus

Incorporating temporal correlation into a multivariate random parameters Tobit model for modeling crash rate by injury severity (2018, background): “…in thepredictionmodels for total crash rate (Ma,Chen, andChen2015), total crash frequency (Lord and Persaud 2000; Wang and Abdel-Aty 2006; Noland, Quddus, and Ochieng 2008; Quddus, 2008; Castro, Paleti, and Bhat 2012; Dong, Huang, et al. 2016), and crash frequency by severity (Chiou and Fu 2015).”
A Model of Ridesourcing Demand Generation and Distribution (2018, background): “If these terms are set to zero, and all elements of the vector βs are also set to zero, the result is the traditional Poisson count model (10).”
Joint Analysis of Injury Severity of Drivers in Two-Vehicle Crashes Accommodating Seat Belt Use Endogeneity (2013, background): “, 2008, and Castro et al., 2012). Savolainen et al. (2011) and Castro et al. (2012) discuss in detail the advantages and limitations of each approach.”
Modeling over-dispersed crash data with a long tail: Examining the accuracy of the dispersion parameter in Negative Binomial models (2015, background): “…Markov switching models (Park and Lord, 2009; Malyshkina et al., 2009; Zou et al., 2013b; Zou et al., 2014), generalized ordered-response models (Castro et al., 2012; Bhat et al., 2014) and quantile regression models (Qin and Reyes, 2011) have been proposed for analyzing the crash-frequency…”
Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review (2014, background): “In fact, in a recent paper (Castro et al., 2012) the authors’ show that count models can be appropriately recast as ordered response models, providing further evidence that ordered models are more appropriate when the universal choice set is comprised of small number of categories.”
A New Generalized Heterogeneous Data Model (GHDM) to Jointly Model Mixed Types of Dependent Variables (2015, methodology): “A second common approach to joint mixed outcome modeling originates in the general location model (GLOM), which assumes an arbitrary marginal distribution for the discrete outcomes and a conditional (on the discrete component) normality assumption for the continuous outcomes (De Leon and Chough, 201”
Jointly modeling area-level crash rates by severity: a Bayesian multivariate random-parameters spatio-temporal Tobit regression (2019, unknown): “…Zeng et al. 2018b), multivariate temporal modeling (Zeng et al. 2018a), and univariate spatio-temporal modeling (Aguero-Valverde and Jovanis 2006; Castro, Paleti, and Bhat 2012; Cheng et al. 2018c; Dong et al. 2016b; Wang, Quddus, and Ison 2013), multivariate spatio-temporal analysis is scarce…”