References
- Andersen, P. K., Borgan, O., Gill, R. D. and Keiding, N. (1993). Statistical models based on counting processes, Springer, New York.
- Anderson, R. M. and May, R. M. (1991). Infectious diseases of humans: Dynamics and control, Clarendon Press, Oxford.
- Andersson, H. and Britton, T. (2000). Stochastic epidemic models and their statistical analysis, Springer-Verlag, New York.
- Bailey, N. T. J. (1975) The mathematical theory of infectious diseases and its applications, Griffin, London.
- Becker, N. G. and Britton, T. (1999). Statistical studies of infectious disease incidence. Journal of the Royal Statistical Society B, 61, 287–307. https://doi.org/10.1111/1467-9868.00177
- Cauchemez, S. and Ferguson, N. M. (2008). Likelihood based estimation of continuous-time epidemic models from time-series data: Application to measles transmission in London. Journal of the Royal Society Interface, 5, 885–897. https://doi.org/10.1098/rsif.2007.1292
- Daley, D. J., Gani, J. (1999). Epidemic modelling: An introduction, Cambridge University Press, New York.
- Diekmann, O. and Heesterbeek, J. A. P. (2000). Mathematical epidemiology of infectious diseases: Model building, analysis and interpretation, Wiley, New York.
- Ha, I. and Cho, G. (2012). H-likelihood approach for variable selection in gamma frailty models. Journal of the Korean Data & Information Science Society, 23, 199-207. https://doi.org/10.7465/jkdi.2012.23.1.199
- Hohle, M. and Jorgensen, E. (2002). Estimating parameters for stochastic epidemics, Dina research report No. 102, Danish Institute of Agricultural Sciences, Research Centre Foulum, Denmark.
- Huggins, M., Yip, P. S. F. and Lau, E. H. Y. (2004). A note on the estimation of the initial number of susceptible individuals in the general epidemic model. Statistics & Probability Letters, 67, 321-330. https://doi.org/10.1016/j.spl.2002.02.001
- Kang, S. G., Lee, J. H. and Lee, W. D. (2012). Likelihood based inference for the ratio of parameters in two Maxwell distributions. Journal of the Korean Data & Information Science Society, 23, 89-98. https://doi.org/10.7465/jkdi.2012.23.1.089
- Kypraios, T. (2009). A note on maximum likelihood estimation of the initial number of susceptibles in the general stochastic epidemic model. Statistics & Probability Letters, 79, 1972–1976. https://doi.org/10.1016/j.spl.2009.06.003
- McKendrick, A. G. (1926). Applications of mathematics to medical problems. Proceedings of the Edinburgh Mathematical Society, 44, 98-130.
- Oh, C. (2013). Approximation of estimates in the susceptible-infectious-removed epidemic model. Journal of Mathematics and Statistics, 9, 38-42. https://doi.org/10.3844/jmssp.2013.38.42
- O'Neill, P. D. and Roberts, G. O. (1999). Bayesian inference for partially observed stochastic epidemics, Journal of the Royal Statistical Society A, 162, 121-129. https://doi.org/10.1111/1467-985X.00125
- Rida, W. N. (1991). Asymptotic properties of some estimators for the infection rate in the general stochastic epidemic model. Journal of the Royal Statistical Society B, 53, 269-283.
- Schutt, R. (2010). Topics in model-based population inference, Ph.D. thesis, Columbia University, New York.
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