References
- A.M. da Silva, P.E. Degrande, M.G. Fernandes, R. Suekane, and W.M. Zeviani, Impacto de diferentes níveis de desfolha artificial nos estádios fenológicos do algodoeiro, Rev. Ciências Agrárias 35 (2012), pp. 163–172.
- A.H. El Shaarawi, R. Zhu, and H. Joe, Modelling species abundance using the Poisson-Tweedie family, Environmetrics 22(2) (2011), pp. 152–164. doi: 10.1002/env.1036
- U. Gonzales-Barron and F. Butler, Characterisation of within-batch and between-batch variability in microbial counts in foods using Poisson-Gamma and poisson-lognormal regression models, Food Control 22 (2011), pp. 1268–1278. doi: 10.1016/j.foodcont.2011.01.028
- G.K. Grunwald, S.L. Bruce, L. Jiang, M. Strand, and N. Rabinovitch, A statistical model for under or overdispersed clustered and longitudinal count data, Biom. J. 53 (2011), pp. 578–594. doi: 10.1002/bimj.201000076
- G. King, Variance specification in event count models: From restrictive assumptions to a generalized estimator, Am. J. Polit. Sci. 33 (1989), pp. 762–784. doi: 10.2307/2111071
- D. Lord, S.R. Geedipally, and S.D. Guikema, Extension of the application of Conway-Maxwell-Poisson models: Analyzing traffic crash data exhibiting underdispersion, Risk Anal. 30 (2010), pp. 1268–1276. doi: 10.1111/j.1539-6924.2010.01417.x
- D. Lord, S.D. Guikema, and S.R. Geedipally, Application of the Conway-Maxwell-Poisson generalized linear model for analyzing motor vehicle crashes, Accid. Anal. Prev. 40 (2008), pp. 1123–1134.
- B. McShane, M. Adrian, E.T. Bradlow, and P.S. Fader, Count models based on Weibull interarrival times, J. Bus. Econom. Statist. 26 (2008), pp. 369–378. doi: 10.1198/073500107000000278
- J.A Nelder and R.W.M. Wedderburn, Generalized linear models, J. Roy. Stat. Soc. Ser. A 135 (1972), pp. 370–384. doi: 10.2307/2344614
- M.S. Ridout and P. Besbeas, An empirical model for underdispersed count data, Stat. Model. 4 (2004), pp. 77–89. doi: 10.1191/1471082X04st064oa
- N. Toft, G.T. Innocent, D.J. Mellor, and S.W. Reid, The Gamma-Poisson model as a statistical method to determine if micro-organisms are randomly distributed in a food matrix, Food Microbiol. 23 (2006), pp. 90–94. doi: 10.1016/j.fm.2005.01.014
- R. Winkelmann, Duration dependence and dispersion in count-data models, J. Bus. Econom. Statist. 13 (1995), pp. 467–474.
- R. Winkelmann and K. Zimmermann, Count data models for demographic data, Math. Popul. Stud. 4 (1994), pp. 205–221. doi: 10.1080/08898489409525374
- R. Zhu and H. Joe, Modelling heavy-tailed count data using a generalised Poisson-inverse Gaussian family, Statist. Probab. Lett. 79 (2009), pp. 1695–1703. doi: 10.1016/j.spl.2009.04.011