Below are published research articles, recent preprints under peer review and published software.
Bladt, M., & Yslas, J. (2021). matrixdist: Statistics for Matrix Distributions. CRAN
Bladt, M., & Yslas, J. (2020). Inhomogeneous Markov survival regression models. arXiv:2011.03219. pdf
Bladt, M., Albrecher, H., & Beirlant, J. (2020). Trimmed extreme value estimators for censored heavy-tailed data. Preprint.
Bladt, M., & McNeil, A. J. (2020). Time series copula models using d-vines and v-transforms: an alternative to GARCH modelling. arXiv:2006.11088. pdf
Albrecher, H., Bladt, M., & Vatamidou, E. (2020). Efficient simulation of ruin probabilities when claims are mixtures of heavy and light tails. Methodology and Computing in Applied Probability, 1-19. pdf
Albrecher, H., Bladt, M., & Bladt, M. (2020). Multivariate fractional phase–type distributions. Fractional Calculus and Applied Analysis, 23(5), 1431–1451. pdf
Albrecher, H., Bladt, M., & Bladt, M. (2020). Multivariate matrix Mittag–Leffler distributions. Annals of the Institute of Statistical Mathematics, 1-26. pdf
Albrecher, H., Bladt, M., & Bladt, M. (2020). Matrix Mittag–Leffler distributions and modeling heavy-tailed risks. Extremes, 23(3), 425–450. pdf
Bladt, M., Albrecher, H., & Beirlant, J. (2020). Threshold selection and trimming in extremes. Extremes, 23(4), 629–665. pdf
Bladt, M., Albrecher, H., & Beirlant, J. (2019). Combined tail estimation using censored data and expert information. Scandinavian Actuarial Journal, 6, 503-525. pdf
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. pdf
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. link
Albrecher, H., Bäuerle, N., & Bladt, M. (2018). Dividends: From refracting to ratcheting. Insurance: Mathematics and Economics, 83, 47-58. pdf