By Dr Francesco Ungolo

Journal articles

Euthum M; Scherer M; Ungolo F, 2024, 'A neural network approach for the mortality analysis of multiple populations: a case study on data of the Italian population', European Actuarial Journal, 14, pp. 495 - 524, http://dx.doi.org/10.1007/s13385-024-00377-5

Ungolo F; van den Heuvel ER, 2024, 'A Dirichlet process mixture regression model for the analysis of competing risk events', Insurance: Mathematics and Economics, 116, pp. 95 - 113, http://dx.doi.org/10.1016/j.insmatheco.2024.02.004

Ungolo F; Garces LPDM; Sherris M; Zhou Y, 2024, 'AffineMortality: An R package for estimation, analysis, and projection of affine mortality models', Annals of Actuarial Science, http://dx.doi.org/10.1017/S1748499524000149

Ungolo F; Garces LPDM; Sherris M; Zhou Y, 2024, 'Estimation, Comparison, and Projection of Multifactor Age–Cohort Affine Mortality Models', North American Actuarial Journal, 28, pp. 570 - 592, http://dx.doi.org/10.1080/10920277.2023.2238793

Ungolo F; van den Heuvel ER, 2022, 'Inference on latent factor models for informative censoring', Statistical Methods in Medical Research, 31, pp. 801 - 820, http://dx.doi.org/10.1177/09622802211057290

Ungolo F; Kleinow T; Macdonald AS, 2020, 'A hierarchical model for the joint mortality analysis of pension scheme data with missing covariates', Insurance: Mathematics and Economics, 91, pp. 68 - 84, http://dx.doi.org/10.1016/j.insmatheco.2020.01.003

Ungolo F; Christiansen MC; Kleinow T; MacDonald AS, 2019, 'Survival analysis of pension scheme mortality when data are missing', Scandinavian Actuarial Journal, 2019, pp. 523 - 547, http://dx.doi.org/10.1080/03461238.2019.1580610

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