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EM Algorithm for Mixed Poisson and Other Discrete Distributions

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  1. R. D. Baker & I. G. McHale, 2009. "Modelling the probability distribution of prize winnings in the UK National Lottery: consequences of conscious selection," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(4), pages 813-834, October.
  2. Alexander D. Knudson & Tomasz J. Kozubowski & Anna K. Panorska & A. Grant Schissler, 2021. "A flexible multivariate model for high-dimensional correlated count data," Journal of Statistical Distributions and Applications, Springer, vol. 8(1), pages 1-21, December.
  3. Tzougas, George & Hoon, W. L. & Lim, J. M., 2019. "The negative binomial-inverse Gaussian regression model with an application to insurance ratemaking," LSE Research Online Documents on Economics 101728, London School of Economics and Political Science, LSE Library.
  4. Gómez-Déniz, E. & Pérez-Rodríguez, J.V., 2019. "Modelling bimodality of length of tourist stay," Annals of Tourism Research, Elsevier, vol. 75(C), pages 131-151.
  5. Kokonendji, Célestin C. & Puig, Pedro, 2018. "Fisher dispersion index for multivariate count distributions: A review and a new proposal," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 180-193.
  6. Peter Congdon, 2020. "Geographical Aspects of Recent Trends in Drug-Related Deaths, with a Focus on Intra-National Contextual Variation," IJERPH, MDPI, vol. 17(21), pages 1-18, November.
  7. Antonio Canale & Igor Prünster, 2017. "Robustifying Bayesian nonparametric mixtures for count data," Biometrics, The International Biometric Society, vol. 73(1), pages 174-184, March.
  8. Muhammed Rasheed Irshad & Christophe Chesneau & Veena D’cruz & Naushad Mamode Khan & Radhakumari Maya, 2022. "Bivariate Poisson 2Sum-Lindley Distributions and the Associated BINAR(1) Processes," Mathematics, MDPI, vol. 10(20), pages 1-24, October.
  9. Veraart, Almut E.D., 2019. "Modeling, simulation and inference for multivariate time series of counts using trawl processes," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 110-129.
  10. Buddhavarapu, Prasad & Scott, James G. & Prozzi, Jorge A., 2016. "Modeling unobserved heterogeneity using finite mixture random parameters for spatially correlated discrete count data," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 492-510.
  11. Tzougas, George & Karlis, Dimitris, 2020. "An EM algorithm for fitting a new class of mixed exponential regression models with varying dispersion," LSE Research Online Documents on Economics 104027, London School of Economics and Political Science, LSE Library.
  12. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
  13. Chen, Zezhun Chen & Dassios, Angelos & Tzougas, George, 2023. "A first order binomial mixed poisson integer-valued autoregressive model with serially dependent innovations," LSE Research Online Documents on Economics 112222, London School of Economics and Political Science, LSE Library.
  14. Aleksandr Bobyl & Oleg Konkov & Mislimat Faradzheva & Igor Kasatkin, 2023. "Using the BWA (Bertaut-Warren-Averbach) Method to Optimize Crystalline Powders Such as LiFePO 4," Mathematics, MDPI, vol. 11(18), pages 1-12, September.
  15. Korolev, Victor & Zeifman, Alexander, 2021. "Bounds for convergence rate in laws of large numbers for mixed Poisson random sums," Statistics & Probability Letters, Elsevier, vol. 168(C).
  16. Chan, Jennifer So Kuen & Wan, Wai Yin, 2014. "Multivariate generalized Poisson geometric process model with scale mixtures of normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 72-87.
  17. Kimberly S. Weems & Paul J. Smith, 2018. "Assessing the robustness of estimators when fitting Poisson inverse Gaussian models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(8), pages 985-1004, November.
  18. Tzougas, George, 2020. "EM estimation for the Poisson-Inverse Gamma regression model with varying dispersion: an application to insurance ratemaking," LSE Research Online Documents on Economics 106539, London School of Economics and Political Science, LSE Library.
  19. Tzougas, George & Pignatelli di Cerchiara, Alice, 2021. "The multivariate mixed Negative Binomial regression model with an application to insurance a posteriori ratemaking," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 602-625.
  20. Mathews Joseph & Bhattacharya Sumangal & Das Ishapathik & Sen Sumen, 2022. "Multiple inflated negative binomial regression for correlated multivariate count data," Dependence Modeling, De Gruyter, vol. 10(1), pages 290-307, January.
  21. Zhang, Pengcheng & Calderin, Enrique & Li, Shuanming & Wu, Xueyuan, 2020. "On the Type I multivariate zero-truncated hurdle model with applications in health insurance," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 35-45.
  22. Jussiane Nader Gonçalves & Wagner Barreto-Souza, 2020. "Flexible regression models for counts with high-inflation of zeros," METRON, Springer;Sapienza Università di Roma, vol. 78(1), pages 71-95, April.
  23. George Tzougas, 2020. "EM Estimation for the Poisson-Inverse Gamma Regression Model with Varying Dispersion: An Application to Insurance Ratemaking," Risks, MDPI, vol. 8(3), pages 1-23, September.
  24. Wen-Han Hwang & Rachel V. Blakey & Jakub Stoklosa, 2020. "Right-Censored Mixed Poisson Count Models with Detection Times," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(1), pages 112-132, March.
  25. Sunisa Junnumtuam & Sa-Aat Niwitpong & Suparat Niwitpong, 2022. "A Zero-and-One Inflated Cosine Geometric Distribution and Its Application," Mathematics, MDPI, vol. 10(21), pages 1-22, October.
  26. Martel-Escobar, M. & Hernández-Bastida, A. & Vázquez-Polo, F.J., 2012. "On the independence between risk profiles in the compound collective risk actuarial model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(8), pages 1419-1431.
  27. Walguen Oscar & Jean Vaillant, 2021. "Cox Processes Associated with Spatial Copula Observed through Stratified Sampling," Mathematics, MDPI, vol. 9(5), pages 1-13, March.
  28. Xiao Li & Michele Guindani & Chaan S. Ng & Brian P. Hobbs, 2021. "A Bayesian nonparametric model for textural pattern heterogeneity," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(2), pages 459-480, March.
  29. Chen, Roger B., 2018. "Models of count with endogenous choices," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 862-875.
  30. Pai, Jeffrey & Li, Yunxian & Yang, Aijun & Li, Chenxu, 2022. "Earthquake parametric insurance with Bayesian spatial quantile regression," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 1-12.
  31. Ong, Seng-Huat & Lee, Wen-Jau & Low, Yeh-Ching, 2020. "A general method of computing mixed Poisson probabilities by Monte Carlo sampling," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 170(C), pages 98-106.
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