References
- Adamids, L. and Loukas, S. (1994). ML estimation in the bivariate Poisson distribution in the presence of missing values via the EM algorithm. Journal of Statistical Computation and Simulation, 50, 163-172. https://doi.org/10.1080/00949659408811608
- Akman, V. E. and Raftery, A. E. (1986). Bayes factors fornon-homogeneous Poisson processes with vague prior information. Journal of the Royal Statistical Society Series B, 48, 322-329.
- Babkov, V. F. (1968). Road design and traffic safety. Traffic Engineering and Control, 236-239.
- Bijleveld, F. D. (2005). The covariance between the number of accidents and the number of victims in multivariate analysis of accident related outcomes. Accident Analysis & Prevention, 37, 591-600. https://doi.org/10.1016/j.aap.2005.01.004
- Garber, N. J. and Gadirau, R. (1988). Speed variance and its in uence on accidents, AAA Foundation for Traffic Safety, Washington, DC.
- Gelfand, A. E. and Smith, A. F. M. (1990). Sampling based approaches to calculating marginal densities. Journal of American Statistical Association, 85, 398-409. https://doi.org/10.1080/01621459.1990.10476213
- Gelman, A. and Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical Science, 7, 457-472. https://doi.org/10.1214/ss/1177011136
- Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Transaction on Pattern Analysis and Machine Intelligence, 6, 721-741. https://doi.org/10.1109/TPAMI.1984.4767596
- Jovanis, P. P. and Chang, H. L. (1986). Modelling the relationship of accidents to miles travelled. Transportation Research Record, 1068, 42-51.
- Kim, D. and Jeong, H. C. (2006). Multivariate Poisson distribution generated via reduction from indepen- dent Poisson variates. Journal of the Korean Data & Information Science Society, 17, 953-961.
- Kim, D., Jeong, H. C. and Jung, B. C. (2006). On the multivariate Poisson distribution with specic covariance matrix. Journal of the Korean Data & Information Science Society, 17, 161-171.
- Lord, D. and Persaud, B. N. (2004). Estimating the safety performance of urban road transportation networks. Accident Analysis & Prevention, 36, 609-620. https://doi.org/10.1016/S0001-4575(03)00069-1
- Ma, J. and Kockelman, K. M. (2006). Bayesian multivariate Poisson regression for models of injury count, by severity. Transportation Research Record, 1950, 24-34. https://doi.org/10.3141/1950-04
- Papageorgiou, H. and Loukas, S. (1988). Conditional even point estimation for bivariate discrete distribu- tions. Communications in Statistics-Theory and Methods, 17, 3403-3412. https://doi.org/10.1080/03610928808829811
- Persaud, B. N. (1991). Estimating accident potential of Ontario road sections. Transportation Research Record, 1327, 47-53.
- Persaud, B. N. (1994). Accident prediction models for rural roads. Canadian Journal of Civil Engineering, 21, 547-554. https://doi.org/10.1139/l94-056
- Persaud, B. N. and Dzbik, L. (1993). Accident prediction models for freeways. Transportation Research Record, 1401, 55-60.
- Smith, A. F. M. and Spiegelhalter, D. J. (1980). Bayes factors and choice criteria for linear models. Journal of the Royal Statistical Society Series B, 42, 213-220.
- Spiegelhalter, D. J. and Smith, A. F. M. (1982). Bayes factors for linear and log-linear models with vague prior information. Journal of the Royal Statistical Society Series B, 44, 377-387.
- Tsionas, E. G. (2001). Bayesian multivariate Poisson regression. Communications in Statistics-Theory and Methods, 30, 243-255. https://doi.org/10.1081/STA-100002028
- Tunaru, R. (2002). Hierarchical Bayesian models for multiple count data. Austrian Journal of Statistics, 31, 221-229.
- Zeger, S. L. and Karim, M. R. (1991). Generalized linear models with random effect: A Gibbs sampling. Journal of the American Statistical Association, 86, 79-86. https://doi.org/10.1080/01621459.1991.10475006