LSE creators

Number of items: 21.
Centre for Philosophy of Natural and Social Sciences (CPNSS)
  • Tzougas, George, Makariou, Despoina (2022). The multivariate Poisson-Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters. Risk Management and Insurance Review, 25(4), 401 - 417. https://doi.org/10.1111/rmir.12224 picture_as_pdf
    • Statistics
  • Zhang, Pengcheng, Chen, Zezhun, Tzougas, George, Calderín–Ojeda, Enrique, Dassios, Angelos, Wu, Xueyuan (2025). Multivariate zero-inflated INAR(1) model with an application in automobile insurance. North American Actuarial Journal, 29(2), 310 - 328. https://doi.org/10.1080/10920277.2024.2381726 picture_as_pdf
  • Chen, Zezhun Chen, Dassios, Angelos, Tzougas, George (2024). EM estimation for bivariate mixed poisson INAR(1) claim count regression models with correlated random effects. European Actuarial Journal, 14(1), 225 – 255. https://doi.org/10.1007/s13385-023-00351-7 picture_as_pdf
  • Chen, Zezhun Chen, Dassios, Angelos, Tzougas, George (2023). INAR approximation of bivariate linear birth and death process. Journal of Applied Statistics, 26(3), 459 - 497. https://doi.org/10.1007/s11203-023-09289-9 picture_as_pdf
  • Chen, Zezhun Chen, Dassios, Angelos, Tzougas, George (2023). A first order binomial mixed poisson integer-valued autoregressive model with serially dependent innovations. Journal of Applied Statistics, 50(2), 352 - 369. https://doi.org/10.1080/02664763.2021.1993798 picture_as_pdf
  • Tzougas, George, Makariou, Despoina (2022). The multivariate Poisson-Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters. Risk Management and Insurance Review, 25(4), 401 - 417. https://doi.org/10.1111/rmir.12224 picture_as_pdf
  • Chen, Zezhun, Dassios, Angelos, Tzougas, George (2022). Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression. Computational Statistics, https://doi.org/10.1007/s00180-022-01253-0 picture_as_pdf
  • Chen, Zezhun, Dassios, Angelos, Tzougas, George (2022). EM estimation for the bivariate mixed exponential regression model. Risks, 10(5). https://doi.org/10.3390/risks10050105 picture_as_pdf
  • Tzougas, George, Hong, Natalia, Ho, Ryan (2022). Mixed poisson regression models with varying dispersion arising from non-conjugate mixing distributions. Algorithms, 15(1). https://doi.org/10.3390/a15010016 picture_as_pdf
  • 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, 101, 602-625. https://doi.org/10.1016/j.insmatheco.2021.10.001
  • Tzougas, George, di Cerchiara, Alice Pignatelli (2021). Bivariate mixed Poisson regression models with varying dispersion. North American Actuarial Journal, https://doi.org/10.1080/10920277.2021.1978850 picture_as_pdf
  • Makariou, Despoina, Barrieu, Pauline, Tzougas, George (2021). A finite mixture modelling perspective for combining experts’ opinions with an application to quantile-based risk measures. Risks, 9(6). https://doi.org/10.3390/risks9060115 picture_as_pdf
  • Tzougas, George, Jeong, Himchan (2021). An expectation-maximization algorithm for the exponential-generalized inverse Gaussian regression model with varying dispersion and shape for modelling the aggregate claim amount. Risks, 9(1), 1-17. https://doi.org/10.3390/risks9010019 picture_as_pdf
  • Tzougas, George (2020). EM estimation for the Poisson-Inverse Gamma regression model with varying dispersion: an application to insurance ratemaking. Risks, 8(3), 1-23. https://doi.org/10.3390/risks8030097 picture_as_pdf
  • Tzougas, George, Karlis, Dimitris (2020). An EM algorithm for fitting a new class of mixed exponential regression models with varying dispersion. ASTIN Bulletin, 50(2), 555 - 583. https://doi.org/10.1017/asb.2020.13 picture_as_pdf
  • Tzougas, George, Hoon, W. L., Lim, J. M. (2019). The negative binomial-inverse Gaussian regression model with an application to insurance ratemaking. European Actuarial Journal, 9(1), 323 - 344. https://doi.org/10.1007/s13385-018-0186-2 picture_as_pdf
  • Tzougas, George, Yik, Woo Hee, Mustaqeem, Muhammad Waqar (2019). Insurance ratemaking using the Exponential-Lognormal regression model. Annals of Actuarial Science, 1 - 30. https://doi.org/10.1017/S1748499519000034 picture_as_pdf
  • Tzougas, George, Vrontos, Spyridon, Frangos, Nicholas (2018). Bonus-Malus systems with two component mixture models arising from different parametric families. North American Actuarial Journal, https://doi.org/10.1080/10920277.2017.1368398
  • Tzougas, George, Karlis, Dimitris, Frangos, Nicholas (2017). Confidence intervals of the premiums of optimal Bonus Malus Systems. Scandinavian Actuarial Journal, 2018(2), 129-144. https://doi.org/10.1080/03461238.2017.1307267
  • Tzougas, George, Vrontos, Spyridon D., Frangos, Nickolaos E. (2015). Risk classification for claim counts and losses using regression models for location, scale and shape. Variance, 9(1), 140-157.
  • Tzougas, George, Vrontos, Spyridon, Frangos, Nicholas (2014). Optimal Bonus-Malus Systems using finite mixture models. ASTIN Bulletin, 44(2), 417-444. https://doi.org/10.1017/asb.2013.31
  • Tzougas, George, Frangos, Nicholas (2014). The design of an optimal Bonus-Malus System based on the Sichel distribution. In Silvestrov, Dmitrii, Martin-Löf, Anders (Eds.), Modern Problems in Insurance Mathematics . Springer International (Firm). picture_as_pdf