Aldrich, J. (1997). “R. A. Fisher and the Making of Maximum Likelihood, 1912–1922.” Statistical Science 12:162–176.
Breslow, N. E. (1984). “Extra-Poisson Variation in Log-Linear Models.” Journal of the Royal Statistical Society, Series C 33:38–44.
Cameron, A. C., and Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge: Cambridge University Press.
Celeux, G., Forbes, F., Robert, C. P., and Titterington, D. M. (2006). “Deviance Information Criteria for Missing Data Models.” Bayesian Analysis 1:651–674.
Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977). “Maximum Likelihood from Incomplete Data via the EM Algorithm.” Journal of the Royal Statistical Society, Series B 39:1–38.
Dennis, J. E., Gay, D. M., and Welsch, R. E. (1981). “An Adaptive Nonlinear Least-Squares Algorithm.” ACM Transactions on Mathematical Software 7:348–368.
Dennis, J. E., and Mei, H. H. W. (1979). “Two New Unconstrained Optimization Algorithms Which Use Function and Gradient Values.” Journal of Optimization Theory and Applications 28:453–482.
Eskow, E., and Schnabel, R. B. (1991). “Algorithm 695: Software for a New Modified Cholesky Factorization.” ACM Transactions on Mathematical Software 17:306–312.
Everitt, B. S., and Hand, D. J. (1981). Finite Mixture Distributions. London: Chapman & Hall.
Ferrari, S. L. P., and Cribari-Neto, F. (2004). “Beta Regression for Modelling Rates and Proportions.” Journal of Applied Statistics 31:799–815.
Fisher, R. A. (1921). “On the 'Probable Error' of a Coefficient of Correlation Deduced from a Small Sample.” Metron 1:3–32.
Fletcher, R. (1987). Practical Methods of Optimization. 2nd ed. Chichester, UK: John Wiley & Sons.
Frühwirth-Schnatter, S. (2006). Finite Mixture and Markov Switching Models. New York: Springer.
Gamerman, D. (1997). “Sampling from the Posterior Distribution in Generalized Linear Models.” Statistics and Computing 7:57–68.
Gay, D. M. (1983). “Subroutines for Unconstrained Minimization.” ACM Transactions on Mathematical Software 9:503–524.
Geweke, J. (1992). “Evaluating the Accuracy of Sampling-Based Approaches to Calculating Posterior Moments.” In Bayesian Statistics, vol. 4, edited by J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, 169–193. Oxford: Clarendon Press.
Griffiths, D. A. (1973). “Maximum Likelihood Estimation for the Beta-Binomial Distribution and an Application to the Household Distribution of the Total Number of Cases of a Disease.” Biometrics 29:637–648.
Haseman, J. K., and Kupper, L. L. (1979). “Analysis of Dichotomous Response Data from Certain Toxicological Experiments.” Biometrics 35:281–293.
Joe, H., and Zhu, R. (2005). “Generalized Poisson Distribution: The Property of Mixture of Poisson and Comparison with Negative Binomial Distribution.” Biometrical Journal 47:219–229.
Kass, R. E., Carlin, B. P., Gelman, A., and Neal, R. M. (1998). “Markov Chain Monte Carlo in Practice: A Roundtable Discussion.” American Statistician 52:93–100.
Lawless, J. F. (1987). “Negative Binomial and Mixed Poisson Regression.” Canadian Journal of Statistics 15:209–225.
Margolin, B. H., Kaplan, N. L., and Zeiger, E. (1981). “Statistical Analysis of the Ames Salmonella Microsome Test.” Proceedings of the National Academy of Sciences 76:3779–3783.
McLachlan, G. J., and Peel, D. (2000). Finite Mixture Models. New York: John Wiley & Sons.
Moré, J. J. (1978). “The Levenberg-Marquardt Algorithm: Implementation and Theory.” In Lecture Notes in Mathematics, vol. 30, edited by G. A. Watson, 105–116. Berlin: Springer-Verlag.
Moré, J. J., and Sorensen, D. C. (1983). “Computing a Trust-Region Step.” SIAM Journal on Scientific and Statistical Computing 4:553–572.
Morel, J. G., and Nagaraj, N. K. (1993). “A Finite Mixture Distribution for Modelling Multinomial Extra Variation.” Biometrika 80:363–371.
Morel, J. G., and Neerchal, N. K. (1997). “Clustered Binary Logistic Regression in Teratology Data Using a Finite Mixture Distribution.” Statistics in Medicine 16:2843–2853.
Neerchal, N. K., and Morel, J. G. (1998). “Large Cluster Results for Two Parametric Multinomial Extra Variation Models.” Journal of the American Statistical Association 93:1078–1087.
Pearson, K. (1915). “On Certain Types of Compound Frequency Distributions in Which the Components Can Be Individually Described by Binomial Series.” Biometrika 11:139–144.
Raftery, A. E. (1996). “Hypothesis Testing and Model Selection.” In Markov Chain Monte Carlo in Practice, edited by W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, 163–188. London: Chapman & Hall.
Richardson, S. (2002). “Discussion of Spiegelhalter et al.” Journal of the Royal Statistical Society, Series B 64:631.
Roeder, K. (1990). “Density Estimation with Confidence Sets Exemplified by Superclusters and Voids in the Galaxies.” Journal of the American Statistical Association 85:617–624.
Spiegelhalter, D. J., Best, N. G., Carlin, B. P., and Van der Linde, A. (2002). “Bayesian Measures of Model Complexity and Fit.” Journal of the Royal Statistical Society, Series B 64:583–616. With discussion.
Titterington, D. M., Smith, A. F. M., and Makov, U. E. (1985). Statistical Analysis of Finite Mixture Distributions. New York: John Wiley & Sons.
Viallefont, V., Richardson, S., and Greene, P. J. (2002). “Bayesian Analysis of Poisson Mixtures.” Journal of Nonparametric Statistics 14:181–202.
Wang, P., Puterman, M. L., Cockburn, I., and Le, N. (1996). “Mixed Poisson Regression Models with Covariate Dependent Rates.” Biometrics 52:381–400.
Williams, D. A. (1975). “The Analysis of Binary Responses from Toxicological Experiments Involving Reproduction and Teratogenicity.” Biometrics 31:949–952.