References
- Alfò, M., Trovato, G. (2004). Semiparametric mixture models for multivariate count data, with application. Econ. J. 7:426–454.
- Cameron, A.C., Johansson, P. (1997). Count data regression using series expansion: with applications. J. Appl. Econ. 12:203–223.
- Cameron, A.C., Li, T., Trivedi, P.K., Zimmer, D.M. (2004). Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts. Econ. J. 7:566–584.
- Cameron, A.C., Trivedi, P.K. (1998). Regression Analysis of Count Data. New York, NY: Cambridge University Press.
- Cameron, A.C., Trivedi, P.K., Milne, F., Piggott, J. (1988). A microeconomic model of the demand for health care and health insurance in Australia. Rev. Econ. Stud. LV:85–106.
- Chib, S., Winkelmann, R. (2001). Markov chain Monte Carlo analysis of correlated count data. J. Bus. Econ. Stat. 19:428–435.
- Consul, P.C. (1989). Generalized Poisson Distributions: Properties and Applications. New York, NY: Marcel Dekker, Inc.
- Consul, P.C., Shoukri, M.M. (1985). The generalized Poisson distribution when the sample mean is larger than the sample variance. Commun. Stat. Theory Methods 14:667–681.
- Famoye, F. (2010a). On the bivariate negative binomial regression model. J. Appl. Stat. 37(6):969–981.
- Famoye, F. (2010b). A new bivariate generalized Poisson distribution. Stat. Neerland. 64(1):112–124.
- Famoye, F., Okafor, R., Adamu, M.O. (2011). A multivariate generalized Poisson distribution. J. Stat. Theory Appl. 10(3):519–531.
- Gurmu, S., Elder, J. (2000). Generalized bivariate count data regression models. Econ. Lett. 68:31–36.
- Hofer, V., Leitner, J. (2012). A bivariate Sarmanov regression model for count data with generalized Poisson marginals. J. Appl. Stat. doi:10.1080/0266473.2012.724661
- Joe, H., Hu, T. (1996). Multivariate distributions from mixtures of max-infinitely divisible distributions. J. Multivar. Anal. 57:240–265.
- Karlis, D. (2003). An EM algorithm for multivariate Poisson distribution and related models. J. Appl. Stat. 30:63–67.
- Karlis, D., Meligkotsidou, L. (2005). Multivariate Poisson regression with covariance structure. Stat. Comput. 15:255–265.
- Kocherlakota, S., Kocherlakota, K. (1992). Bivariate Discrete Distributions. New York, NY: Marcel Dekker, Inc.
- Lakshminarayana, J., Pandit, S.N.N., Rao, K.S. (1999). On a bivariate Poisson distribution. Commun. Stat. Theory Methods 28:267–276.
- Lee, A. (1999). Modelling rugby league data via bivariate negative binomial regression. Austral. N. Z. J. Stat. 41:141–152.
- Lee, M.-L.T. (1996). Properties and applications of the Sarmanov family of bivariate distributions. Commun. Stat. Theory Methods 25:1207–1222.
- Ma, J., Kockelman, K.M., Damien, P. (2008). A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods. Accid. Anal. Prevent. 40:964–975.
- Miravete, E.J. (2009). Multivariate Sarmanov count data models. CEPR Discussion Paper No. DP7463. London: Centre for Economic Policy Research (CEPR).
- Mullahy, J. (1997). Heterogeneity, excess zeros, and the structure of count data models. J. Appl. Econ. 12:337–350.
- National Health and Nutrition Examination Survey (NHANES). (2007–2008) [Computer file]. ICPSR25505-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2010-05-04. 10.3886/ICPSR25505
- Nikoloulopoulos, A.K., Karlis, D. (2010). Modeling multivariate count data using copulas. Commun. Stat. Simul. Comput. 39:172–187.
- Sarmanov, O.V. (1966). Generalized normal correlation and two-dimensional Fréchet classes. Soviet Math. Doklady 168:596–599.
- Winkelmann, R. (2008). Econometric Analysis of Count Data (5th ed.). Berlin: Springer Verlag.
- van Ophem, H. (1999). A general method to estimate correlated discrete random variables. Econ. Theory 15:228–237.
- Zimmer, D., Trivedi, P. (2006). Using trivariate copulas to model sample selection and treatment effects: application to family health care demand. J. Bus. Econ. Stat. 24:63–74.