By Dr Francesco Ungolo

Book Chapters

Ungolo F; Kleinow T; Macdonald AS, 2021, 'Parametric Bootstrap Estimation of Standard Errors in Survival Models When Covariates are Missing', in Mathematical and Statistical Methods for Actuarial Sciences and Finance eMAF2020, Springer, pp. 389 - 394, http://dx.doi.org/10.1007/978-3-030-78965-7

Ungolo F; Kleinow T; Macdonald AS, 2021, 'Parametric bootstrap estimation of standard errors in survival models when covariates are missing', in Mathematical and Statistical Methods for Actuarial Sciences and Finance Emaf2020, pp. 389 - 394, http://dx.doi.org/10.1007/978-3-030-78965-7_57

Journal articles

Den Teuling NGP; Ungolo F; Pauws SC; van den Heuvel ER, 2025, 'Latent-class trajectory modeling with a heterogeneous mean-variance relation', Computational Statistics and Data Analysis, 210, http://dx.doi.org/10.1016/j.csda.2025.108199

Ungolo F; Laub P, 2024, 'An Augmented Variable Dirichlet Process mixture model for the analysis of dependent lifetimes', ASTIN Bulletin, 55, pp. 50 - 75, http://dx.doi.org/10.1017/asb.2024.34

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, 19, pp. 23 - 48, 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

Working Papers

Garces LP; Kolar J; Sherris M; Ungolo F, 2022, Affine Mortality Models with Jumps: Parameter Estimation and Forecasting, CEPAR Working Paper 2022/12, http://dx.doi.org, https://cepar.edu.au/publications/working-papers/affine-mortality-models-jumps-parameter-estimation-and-forecasting

Preprints

Garces LPD; Kolar J; Sherris M; Ungolo F, Affine Mortality Models with Jumps: Parameter Estimation and Forecasting, http://dx.doi.org/10.2139/ssrn.4220454

Ungolo F; Sherris M; Zhou Y, affine_mortality: A Github repository for estimation, analysis, and projection of affine mortality models, http://dx.doi.org/10.2139/ssrn.3912983

Ungolo F, An Augmented Variable Dirichlet Process Mixture Model for the Analysis of Dependent Lifetimes, http://dx.doi.org/10.2139/ssrn.4428250

Ungolo F; Sherris M; Zhou Y, Multi-factor, Age-Cohort, Affine Mortality Models: A Multi-Country Comparison, http://dx.doi.org/10.2139/ssrn.3912981

Cottrell PE; Ungolo F, Utilizing Topographic Finance to Understand Volatility, http://dx.doi.org/10.2139/ssrn.2590405

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