Publications

Published peer-reviewed articles

Bladt, M., & Shaiderman, D. (2023). Characterisation of exchangeable sequences through empirical distributions. Electronic Communications in Probability, to appear. arXiv:1903.07861.
Ahmad, J., Bladt, M., & Bladt, M. (2023). Estimating absorption time distributions of general Markov jump processes. Scandinavian Journal of Statistics, to appear. arXiv:2207.11303.
Bladt, M., & Furrer, C. (2023). Expert Kaplan–Meier estimation. Scandinavian Actuarial Journal, 1-27. doi:10.1080/03461238.2023.2197442, arXiv:2206.13120.
Bladt, M., & Yslas, J. (2023). Robust claim frequency modeling through phase-type mixture-of-experts regression. Insurance: Mathematics and Economics, 111, 1-22. doi:10.1016/j.insmatheco.2023.02.008, ssrn:4310567.
Bladt, M., & Yslas, J. (2023). Phase-type mixture-of-experts regression for loss severities. Scandinavian Actuarial Journal, 2023(4), 303-329. doi:10.1080/03461238.2022.2097019, arXiv:2111.00581.
Bladt, M., & Brimnes Gardner, C. (2023). Joint discrete and continuous matrix distribution modelling. Stochastic Models, 1-37. doi:10.1080/15326349.2023.2185257, arXiv:2207.01364.
Bladt, M. (2023). A tractable class of Multivariate Phase-type distributions for loss modeling. North American Actuarial Journal, 1-21. doi:10.1080/10920277.2023.2167833, arXiv:2110.05179.
Albrecher, H., Bladt, M., & Mueller, A. (2023). Joint lifetime modelling with matrix distributions. Dependence Modeling, 11(1), 1-22. doi:10.1515/demo-2022-0153, arXiv:2207.01279.
Bladt, M., Fuino, M., Shemendyuk, A., & Wagner, J. (2023). Modeling the Burden of Long-Term Care for Institutionalized Elderly Based on Care Duration and Intensity. Annals of Actuarial Science, 17(1): 83-117. doi:10.1017/S1748499522000136.
Albrecher, H., Bladt, M., & Mueller, A. (2022). Penalised likelihood methods for phase-type dimension selection. Statistics & Risk Modeling, 39(3-4), 75-92. doi:10.1515/strm-2021-0026.
Albrecher, H., Bladt, M., Bladt, M. & Yslas, J. (2022). Mortality modeling and regression with matrix distributions. Insurance: Mathematics and Economics, 107, 68-87. doi:10.1016/j.insmatheco.2022.08.001, arXiv:2011.03219.
Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2022). Continuous scaled phase-type distributions. Stochastic Models, 1-30. doi:10.1080/15326349.2022.2089683, arXiv:2103.02457.
Bladt, M., Hashorva, E., & Shevchenko, G. (2022). Tail Measures and Regular Variation. Electronic Journal of Probability, 27, 1-43. doi:10.1214/22-EJP788, arXiv:2103.04396.
Bladt, M., & McNeil, A. J. (2022). Time series models with infinite-order partial copula dependence. Dependence Modeling, 10(1), 87-107. doi:10.1515/demo-2022-0105, arXiv:2107.00960.
Bladt, M., & Yslas, J. (2022). Heavy-tailed phase-type distributions: a unified approach. Extremes, 1-37. doi:10.1007/s10687-022-00436-8, arXiv:2107.09023.
Bladt, M. (2022). Phase-type distributions for claim severity regression modeling. ASTIN Bulletin: The journal of the IAA, 52(2), 417-448. doi:10.1017/asb.2021.40, arXiv:2110.05207.
Bladt, M. (2021). Fractional inhomogeneous multi-state models in life insurance. Scandinavian Actuarial Journal, 1-22. doi:10.1080/03461238.2021.1998921, arXiv:2110.05199.
Bladt, M., & McNeil, A. J. (2021). Time series copula models using d-vines and v-transforms. Econometrics and Statistics, 24, 27-48. doi:10.1016/j.ecosta.2021.07.004, arXiv:2006.11088.
Bladt, M., Albrecher, H., & Beirlant, J. (2021). Trimmed extreme value estimators for censored heavy-tailed data. Electronic Journal of Statistics, 15(1), 3112-3136. doi:10.1214/21-EJS1857.
Albrecher, H., Bladt, M., & Vatamidou, E. (2021). Efficient simulation of ruin probabilities when claims are mixtures of heavy and light tails. Methodology and Computing in Applied Probability, 23(4), 1237-1255. doi:10.1007/s11009-020-09799-6.
Albrecher, H., Bladt, M., & Bladt, M. (2020). Multivariate fractional phase-type distributions. Fractional Calculus and Applied Analysis, 23(5), 1431-1451. doi:10.1515/fca-2020-0071, arXiv:2003.11122.
Albrecher, H., Bladt, M., & Bladt, M. (2020). Multivariate matrix Mittag–Leffler distributions. Annals of the Institute of Statistical Mathematics, 1-26. doi:10.1007/s10463-020-00750-7.
Albrecher, H., Bladt, M., & Bladt, M. (2020). Matrix Mittag–Leffler distributions and modeling heavy-tailed risks. Extremes, 23(3), 425-450. doi:10.1007/s10687-020-00377-0.
Bladt, M., Albrecher, H., & Beirlant, J. (2020). Threshold selection and trimming in extremes. Extremes, 23(4), 629-665. doi:10.1007/s10687-020-00385-0.
Bladt, M., Albrecher, H., & Beirlant, J. (2019). Combined tail estimation using censored data and expert information. Scandinavian Actuarial Journal, 6, 503-525. doi:10.1080/03461238.2019.1694974.
Daily-Amir, D., Albrecher, H., Bladt, M., & Wagner, J. (2019). On Market Share Drivers in the Swiss Mandatory Health Insurance Sector. Risks, 7(4), 114. doi:10.3390/risks7040114.
Albrecher, H., Bladt, M., Kortschak, D., Prettenthaler, F., & Swierczynski, T. (2019). Flood occurrence change-point analysis in the paleoflood record from Lake Mondsee (NE Alps). Global and Planetary Change, 178, 65-76. doi:10.1016/j.gloplacha.2019.04.009.
Albrecher, H., Bäuerle, N., & Bladt, M. (2018). Dividends: From refracting to ratcheting. Insurance: Mathematics and Economics, 83, 47-58. doi:10.1016/j.insmatheco.2018.09.003.

Submitted manuscripts

Bladt, M., & Furrer, C. Conditional Aalen–Johansen estimation. Preprint, University of Copenhagen. arXiv:2303.02119.
Bladt, M., Dias, A., Han, J., & McNeil, A. J. Semiparametric forecasting using non-Gaussian ARMA models based on s-vines. Preprint, University of Copenhagen, University of York.
Beirlant, J., & Bladt, M. Tail Parameter Estimation using Non-Linear Regression on Tail Model Plots. Preprint, KU Leuven, University of Copenhagen. doi:10.21203/rs.3.rs-2638091/v1.
Beirlant, J., Bladt, M., Maribe, G., & Verster, A. Estimation of tail parameters with missing largest observations. Preprint, KU Leuven, University of Copenhagen, University of Pretoria, University of the Free State.
Albrecher, H., & Bladt, M. Informed censoring: the parametric combination of data and expert information. Preprint, University of Lausanne. arXiv:2206.13091.
Bladt, M., & Peralta, O. Strongly convergent homogeneous approximations to inhomogeneous Markov jump processes and applications. Preprint, University of Lausanne. arXiv:2204.02954.
Bladt, M., & Yslas, J. matrixdist: An R package for inhomogeneous phase-type distributions. Preprint, University of Lausanne. arXiv:2101.07987.