Modeling unobserved heterogeneity for zonal crash frequencies: A Bayesian multivariate random-parameters model with mixture components for spatially correlated …
… flexible modeling of heterogeneous data because it can incorporate a combination of discrete
and continuous variations in crash counts. It … density in the multivariate random parameters …
and continuous variations in crash counts. It … density in the multivariate random parameters …
Analyzing road crash frequencies with uncorrelated and correlated random-parameters count models: An empirical assessment of multilane highways
… In an endeavor to advance the state of the art in analytic methods in safety research
characterized by and grappling with unobserved heterogeneity and cross-correlations of random …
characterized by and grappling with unobserved heterogeneity and cross-correlations of random …
[HTML][HTML] Predicting downgrade crash frequency with the random-parameters negative binomial model: Insights into the impacts of geometric variables on downgrade …
… case of the random parameters model) handles unobserved … account for unobserved
heterogeneity in count data models. … random parameters model with flexible discrete densities to …
heterogeneity in count data models. … random parameters model with flexible discrete densities to …
[HTML][HTML] Extensive hypothesis testing for estimation of crash frequency models
… framework to estimate crash data count models, surpassing benchmark models in terms of …
with unobserved heterogeneity using random effects, random parameters, mixing models, and…
with unobserved heterogeneity using random effects, random parameters, mixing models, and…
A random parameters with heterogeneity in means and Lindley approach to analyze crash data with excessive zeros: A case study of head-on heavy vehicle crashes …
… study to factor for the unobserved heterogeneity using additional … While random parameters
have flexible estimation structures… Let, g(.) is the probability density function of ω i , then the …
have flexible estimation structures… Let, g(.) is the probability density function of ω i , then the …
Embracing asymmetry in nature: How to account for skewness in ecological data
… , and ALD probability density functions with parameters set at … Discrete data, including binary
data and count data, do not … can be limited by latent, unobservable environmental factors, …
data and count data, do not … can be limited by latent, unobservable environmental factors, …
A random parameters regional quantile analysis for the varying effect of road-level risk factors on crash rates
… Laplace Distribution, the density function is given by(14) f τ ( y | … of the unobserved
heterogeneity in the modeling crash rate. … hierarchical random parameter Tobit model which is …
heterogeneity in the modeling crash rate. … hierarchical random parameter Tobit model which is …
[HTML][HTML] Estimating the effect of proximity to school on cyclist safety using a simultaneous-equations model with heterogeneity in covariance to address potential …
S Heydari, M Forrest - Analytic Methods in Accident Research, 2024 - Elsevier
… to improve model fit and address unobserved heterogeneity … of the counts for the years
studied in this analysis. Built environment … , a bivariate normal density to model the error terms is …
studied in this analysis. Built environment … , a bivariate normal density to model the error terms is …
On the causal effect of proximity to school on pedestrian safety at signalized intersections: A heterogeneous endogenous econometric model
… , s* is unobservable leading to a binary probit model. In our … The data used in this paper
contain pedestrian injury counts … , we assign a density to the correlation parameter to better …
contain pedestrian injury counts … , we assign a density to the correlation parameter to better …
[HTML][HTML] Copula-based bivariate finite mixture regression models with an application for insurance claim count data
L Bermúdez, D Karlis - TEST, 2022 - Springer
… embraces zero-inflated bivariate Poisson regression models. … The models proposed in this
paper account for unobserved … allowing each component in the discrete mixture to have its …
paper account for unobserved … allowing each component in the discrete mixture to have its …