A multivariate heterogeneous-dispersion count model for asymmetric interdependent freeway crash types
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Toshiyuki Yamamoto | Venkataraman N. Shankar | Ghasak I.M.A. Mothafer | Toshiyuki Yamamoto | V. Shankar
[1] Zhibin Li,et al. Analysis of Crash Risks by Collision Type at Freeway Diverge Area Using Multivariate Modeling Technique , 2015 .
[2] Fred L Mannering,et al. A note on modeling vehicle accident frequencies with random-parameters count models. , 2009, Accident; analysis and prevention.
[3] ON THE RANGE OF CORRELATION COEFFICIENTS OF BIVARIATE ORDERED DISCRETE RANDOM VARIABLES , 2001, Econometric Theory.
[4] Fred L. Mannering,et al. The effect of speed limits on drivers' choice of speed: A random parameters seemingly unrelated equations approach , 2016 .
[5] Sujan Sikder,et al. Copula-Based Method for Addressing Endogeneity in Models of Severity of Traffic Crash Injuries: Application to Two-Vehicle Crashes , 2010 .
[6] H. Joe,et al. Composite likelihood estimation in multivariate data analysis , 2005 .
[7] Moshe Ben-Akiva,et al. Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .
[8] Chandra R. Bhat,et al. Analytic methods in accident research: Methodological frontier and future directions , 2014 .
[9] Chandra R. Bhat,et al. On Jointly Analyzing the Physical Activity Participation Levels of Individuals in a Family Unit , 2010 .
[10] Robert H. Shumway,et al. Time series analysis and its applications : with R examples , 2017 .
[11] Paul Damien,et al. A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods. , 2008, Accident; analysis and prevention.
[12] Chandra R. Bhat,et al. On allowing a general form for unobserved heterogeneity in the multiple discrete–continuous probit model: Formulation and application to tourism travel , 2016 .
[13] James Kuhr,et al. A Model of Ridesourcing Demand Generation and Distribution , 2018 .
[14] Fred L Mannering,et al. An empirical assessment of fixed and random parameter logit models using crash- and non-crash-specific injury data. , 2011, Accident; analysis and prevention.
[15] Srinivas R. Geedipally,et al. A semiparametric negative binomial generalized linear model for modeling over-dispersed count data with a heavy tail: Characteristics and applications to crash data. , 2016, Accident; analysis and prevention.
[16] Chandra R. Bhat,et al. Unobserved heterogeneity and the statistical analysis of highway accident data , 2016 .
[17] Peng Shi,et al. Multivariate Negative Binomial Models for Insurance Claim Counts , 2012 .
[18] Sudip Barua,et al. Multivariate random parameters collision count data models with spatial heterogeneity , 2016 .
[19] Chandra R. Bhat,et al. On Accommodating Spatial Interactions in a Generalized Heterogeneous Data Model (GHDM) of Mixed Types of Dependent Variables , 2016 .
[20] H. Joe. Dependence Modeling with Copulas , 2014 .
[21] Fred L. Mannering,et al. The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives , 2010 .
[22] C. Genest,et al. A Primer on Copulas for Count Data , 2007, ASTIN Bulletin.
[23] C. Bhat,et al. A Flexible Spatially Dependent Discrete Choice Model: Formulation and Application to Teenagers’ Weekday Recreational Activity Participation , 2010 .
[24] Paul P Jovanis,et al. Bayesian Multivariate Poisson Lognormal Models for Crash Severity Modeling and Site Ranking , 2009 .
[25] Chandra R. Bhat,et al. Copula-Based Approach to Accommodate Residential Self-Selection Effects in Travel Behavior Modeling , 2009 .
[26] Subhabrata Chakraborti,et al. Nonparametric Statistical Inference , 2011, International Encyclopedia of Statistical Science.
[27] N. Ravishanker,et al. Multivariate poisson lognormal modeling of crashes by type and severity on rural two lane highways. , 2017, Accident; analysis and prevention.
[28] David M. Zimmer,et al. Modelling the Differences in Counted Outcomes Using Bivariate Copula Models with Application to Mismeasured Counts , 2004 .
[29] Karthik C Konduri,et al. A simultaneous equations model of crash frequency by severity level for freeway sections. , 2013, Accident; analysis and prevention.
[30] V. P. Godambe. An Optimum Property of Regular Maximum Likelihood Estimation , 1960 .
[31] Chandra R. Bhat,et al. Introducing Latent Psychological Constructs in Injury Severity Modeling: Multivehicle and Multioccupant Approach , 2016 .
[32] Satish V. Ukkusuri,et al. An Efficient Parallel Sampling Technique for Multivariate Poisson-Lognormal Model: Analysis with Two Crash Count Datasets , 2015 .
[33] Rajesh Paleti,et al. A Spatial Multivariate Count Model for Firm Location Decisions , 2014 .
[34] Toshiyuki Yamamoto,et al. Evaluating crash type covariances and roadway geometric marginal effects using the multivariate Poisson gamma mixture model , 2016 .
[35] Richard Tay,et al. Examining driver injury severity in two vehicle crashes - a copula based approach. , 2014, Accident; analysis and prevention.
[36] David Pitfield,et al. Predicting the safety impact of a speed limit increase using condition-based multivariate Poisson lognormal regression , 2016 .
[37] Chandra R. Bhat,et al. A copula-based closed-form binary logit choice model for accommodating spatial correlation across observational units , 2009, J. Geogr. Syst..
[38] Chandra R. Bhat,et al. A count data model with endogenous covariates: Formulation and application to roadway crash frequency at intersections , 2014 .
[39] H. Joe. Multivariate Models and Multivariate Dependence Concepts , 1997 .
[40] L. Weissfeld,et al. Application of copulas to improve covariance estimation for partial least squares , 2013, Statistics in medicine.
[41] R. Winkelmann. Copula bivariate probit models: with an application to medical expenditures. , 2012, Health economics.
[42] Chandra R. Bhat,et al. A spatial generalized ordered-response model with skew normal kernel error terms with an application to bicycling frequency , 2017 .
[43] Saudi Arabia,et al. Introducing Non-Normality of Latent Psychological Constructs in Choice Modeling with an Application to Bicyclist Route Choice , 2015 .
[44] Liping Fu,et al. Using a flexible multivariate latent class approach to model correlated outcomes: A joint analysis of pedestrian and cyclist injuries , 2017 .
[45] Paolo Ghirardato,et al. Coping with ignorance: unforeseen contingencies and non-additive uncertainty , 2001 .
[47] Chandra R. Bhat,et al. A new mixed MNP model accommodating a variety of dependent non-normal coefficient distributions , 2017 .
[48] Venkataraman N. Shankar,et al. Transferability Analysis of Heterogeneous Overdispersion Parameter Negative Binomial Crash Models , 2016 .
[49] Lung-fei Lee. Generalized Econometric Models with Selectivity , 1983 .
[50] Pravin K. Trivedi,et al. Using Trivariate Copulas to Model Sample Selection and Treatment Effects , 2006 .
[51] Gudmundur F. Ulfarsson,et al. A heterogeneity-in-means count model for evaluating the effects of interchange type on heterogeneous influences of interstate geometrics on crash frequencies , 2014 .
[52] Chandra R. Bhat,et al. Incorporating a Multiple Discrete-Continuous Outcome in the Generalized Heterogeneous Data Model: Application to Residential Self-Selection Effects Analysis in an Activity Time-use Behavior Model , 2015 .
[53] R. Nelsen. An Introduction to Copulas , 1998 .
[54] Eun Sug Park,et al. Multivariate Poisson-Lognormal Models for Jointly Modeling Crash Frequency by Severity , 2007 .
[55] Yu-Chiun Chiou,et al. Modeling crash frequency and severity using multinomial-generalized Poisson model with error components. , 2013, Accident; analysis and prevention.
[56] Jean-Philippe Boucher,et al. Models for insurance claim count with time dependence based on generalisations of Poisson and Negative Binomial distributions , 2008 .
[57] Mohamed Abdel-Aty,et al. Multivariate crash modeling for motor vehicle and non-motorized modes at the macroscopic level. , 2015, Accident; analysis and prevention.
[58] Pravin K. Trivedi,et al. Regression Analysis of Count Data , 1998 .
[59] Helai Huang,et al. A multivariate random-parameters Tobit model for analyzing highway crash rates by injury severity. , 2017, Accident; analysis and prevention.
[60] Chandra R. Bhat,et al. A New Estimation Approach to Integrate Latent Psychological Constructs in Choice Modeling , 2014 .
[61] Rajesh Paleti,et al. A spatial generalized ordered response model to examine highway crash injury severity. , 2013, Accident; analysis and prevention.
[62] Chandra R. Bhat,et al. The composite marginal likelihood (CML) estimation of panel ordered-response models , 2013 .
[63] E. Frees,et al. Heavy-tailed longitudinal data modeling using copulas , 2008 .
[64] Chandra R. Bhat,et al. On Accommodating Spatial Dependence in Bicycle and Pedestrian Injury Counts by Severity Level , 2013 .
[65] Mohamed Abdel-Aty,et al. Joint Modeling of Pedestrian and Bicycle Crashes: Copula-Based Approach , 2016 .
[66] Chandra R. Bhat,et al. A latent variable representation of count data models to accommodate spatial and temporal dependence: application to predicting crash frequency at intersections , 2011 .
[67] Michel Denuit,et al. Constraints on concordance measures in bivariate discrete data , 2005 .
[68] Fred L Mannering,et al. A multivariate tobit analysis of highway accident-injury-severity rates. , 2012, Accident; analysis and prevention.
[69] R. Winkelmann. Econometric Analysis of Count Data , 1997 .
[70] J. Hüsler. Maxima of normal random vectors: between independence and complete dependence , 1989 .
[71] Meiquan Xie,et al. Comparison of Multivariate Poisson lognormal spatial and temporal crash models to identify hot spots of intersections based on crash types. , 2017, Accident; analysis and prevention.
[72] Dimitris Karlis,et al. Modeling Multivariate Count Data Using Copulas , 2009, Commun. Stat. Simul. Comput..
[73] Harry Joe,et al. Families of min-stable multivariate exponential and multivariate extreme value distributions , 1990 .
[74] Chandra R. Bhat,et al. A Multivariate Ordered-response Model System for Adults' Weekday Activity Episode Generation by Activity Purpose and Social Context , 2010 .
[75] Harry Joe,et al. Composite Likelihood Methods , 2012 .
[76] Chandra R. Bhat,et al. A new spatial and flexible multivariate random-coefficients model for the analysis of pedestrian injury counts by severity level , 2017 .
[77] Chandra R. Bhat,et al. A New Utility-Consistent Econometric Approach to Multivariate Count Data Modeling , 2015 .
[78] Albert W. Marshall,et al. Copulas, marginals, and joint distributions , 1996 .
[79] Baoshan Huang,et al. Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections. , 2014, Accident; analysis and prevention.
[80] E. Lee,et al. Copula Analysis of Correlated Counts , 2014 .
[81] Hans van Ophem,et al. A GENERAL METHOD TO ESTIMATE CORRELATED DISCRETE RANDOM VARIABLES , 1999, Econometric Theory.
[82] Ahmet Tortum,et al. Accident analysis with aggregated data: the random parameters negative binomial panel count data model , 2015 .
[83] Mohamed Abdel-Aty,et al. A combined frequency–severity approach for the analysis of rear-end crashes on urban arterials , 2011 .
[84] K. El-Basyouny,et al. Collision prediction models using multivariate Poisson-lognormal regression. , 2009, Accident; analysis and prevention.