References
- Barbiero, A. 2017a. Discrete Weibull variables linked by Farlie–Gumbel–Morgenstern copula. AIP Conference Proceedings 1863(240006). New York: AIP Publishing.
- Barbiero, A. 2017b A bivariate geometric distribution with positive or negative correlation. AIP Conference Proceedings 1906(110003). New York: AIP Publishing.
- Basu, A. P. 1971. Bivariate failure rate. Journal of the American Statistical Association 66 (333): 103–104.
- Basu, A. P., and S. K. Dhar. 1995. Bivariate geometric distribution. Journal of Applied Statistics Science 2:33–44.
- Bolker, B. 2016. R Development core team. bbmle: Tools for general maximum likelihood estimation. R package version 1.0.18. https://CRAN.R-project.org/package=bbmle
- Bracquemond, C., E. Cretois, and O. Gaudoin. A comparative study of goodness-of-fit tests for the geometric distribution and application to discrete time reliability. Technical Report, Saint Martin d’Héres (France): Laboratoire Jean Kuntzmann, Applied Mathematics and Computer Science.
- Cambanis, S. 1977. Some properties and generalizations of multivariate Eyraud-Gumbel-Morgenstern distributions. J. Multivariate Analysis 7 (4):551–59.
- Dhar, S. K. 1998. Data analysis with discrete analog of Freund’s model. Journal of Applied Statistics Science 7:169–83.
- Famoye, F. 2010. On the bivariate negative binomial regression model. Journal of Applied Statistics 37 (6):969–81.
- Farlie, D. J. G. 1960. The performance of some correlation coefficient for a general bivariate distribution. Biometrika 47:307–23.
- Freund, J. E. 1961. A bivariate extension of the exponential distribution. Journal of American Statistics Association 56:971–77.
- Genest, C., A. Carabarín-Aguirre, and F. Harvey. 2013. Copula parameter estimation using Blomqvist’s beta. Journal de la Société Française de Statistique 154 (1):5–24.
- Gómez-Déniz, E., M. F. Ghitany, and R. C. Gupta. 2017. A bivariate generalized geometric distribution with applications. Communications in Statistics - Theory and Methods 46 (11):5453–65.
- Huber, M., and N. Maric. 2014. Minimum correlation for any bivariate Geometric distribution. Alea 11(1):459–70.
- Joe, H., and J. J. Xu. 1996. The estimation method of inference functions for margins for multivariate models. Technical Report, No. 166. Vancouver (Canada): UBC, Department of Statistics.
- Joe, H. 1997. Multivariate models and dependence concepts. London: Chapman & Hall.
- Johnson, N. L., S. Kotz, and N. Balakrishnan. 1997. Discrete multivariate distributions. New York: Wiley.
- Jovanović, M. 2017. Estimation of P{X<Y} for geometric-exponential model based on complete and censored samples. Communication in Statistics—Simulation and Computation 46 (4):3050–66.
- Kocherlakota, S., and K. Kocherlakota. 1992. Bivariate discrete distributions. New York: Marcel Dekker.
- Krishna, H., and P. S. Pundir. 2009. A bivariate geometric distribution with applications to reliability. Communication in Statistics—Theory and Methods 38 (7):1079–93.
- Li, J., and S. K. Dhar. 2013. Modeling with bivariate geometric distributions. Communications in Statistics—Theory and Methods 42 (2):252–66.
- Maiti, S. S. 1995. Estimation of P(X≤Y) in the geometric case. Journal of Indian Statistical Association 33:87–91.
- Marshall, A. W., and I. Olkin. 1967. A multivariate exponential distribution. Journal of American Statistical Association 62:30–44.
- Mitchell, C. R., and A. S. Paulson. 1981. A new bivariate negative binomial distribution. Naval Research Logistics Quarterly 28:359–74.
- Ng, C. M., S. H. Ong, and H. M. Srivastava. 2010. A class of bivariate negative binomial distributions with different index parameters in the marginals. Applied Mathematics and Computation 217 (7):3069–87.
- Omey, E., and L. D. Minkova. 2013. Bivariate geometric distributions. Comptes rendus de l’Académie bulgare des Sciences 67(9), 1201–1210.
- Paulson, A. S., and V. R. R. Uppuluri. A characterization of the geometric distribution and a bivariate geometric distribution. Sankhyā Series A 297–300.
- Piperigou, V. 2009. Discrete distributions in the extended FGM family. Journal of Statistical Planning Inference 139 (11):3891–99.
- Phatak, A. G., and M. Sreehari. 1981. Some characterizations of a bivariate geometric distribution. Journal of the Indian Statistical Association 19:141–46.
- R Core Team, R. 2017. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. URL https://www.R-project.org/
- Roy, D. 1993. Reliability measures in the discrete bivariate set-up and related characterization results for a bivariate geometric distribution. Journal of Multivariate Analysis 46 (2):362–73.
- Sarabia, J. M., and E. Gómez-Déniz. 2011. Multivariate Poisson-beta distributions with applications. Communication in Statistics—Theory and Methods 40 (6):1093–108.
- Schucany, W., W. C. Parr, and J. E. Boyer. 1978. Correlation structure in Farlie–Gumbel-Morgenstern distributions. Biometrika 65 (3):650–53.
- Venzon, D. J., and S. H. Moolgavkar. 1988. A method for computing profile-likelihood-based confidence intervals. Applied Statistics 37 (1):87–94.