matrixdist-package: Statistics for Matrix Distributions
In matrixdist: Statistics for Matrix Distributions
matrixdist-package R Documentation
Statistics for Matrix Distributions
Description
This package implements tools which are useful for the statistical analysis of discrete, continuous, multivariate, right-censored or regression variants of phase-type distributions. These distributions are absorption times of Markov jump processes, and thus the maximization of their likelihood for statistical estimation is best dealt with using the EM algorithm.
Author(s)
Martin Bladt and Jorge Yslas.
Maintainer: Martin Bladt <martinbladt@gmail.com>
References
Asmussen, S., Nerman, O., & Olsson, M. (1996). Fitting phase-type distributions via the EM
algorithm. Scandinavian Journal of Statistics, 23(4),419-441.
Olsson, M. (1996). Estimation of phase-type distributions from censored data. Scandinavian journal of statistics, 24(4), 443-460.
Albrecher, H., & Bladt, M. (2019). Inhomogeneous phase-type distributions and heavy tails. Journal of Applied Probability, 56(4), 1044-1064.
Albrecher, H., Bladt, M., & Yslas, J. (2022). Fitting inhomogeneous Phase-Type distributions to data: The univariate and the multivariate case. Scandinavian Journal of Statistics, 49(1), 44-77
Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2020). Mortality modeling and regression with matrix distributions. Insurance: Mathematics and Economics, 107, 68-87.
Bladt, M., & Yslas, J. (2022). Phase-type mixture-of-experts regression for loss severities. ScandinavianActuarialJournal, 1-27.
Bladt, M. (2022). Phase-type distributions for claim severity regression modeling. ASTIN Bulletin: The journal of the IAA, 52(2), 417-448.
Bladt, M. (2023). A tractable class of Multivariate Phase-type distributions for loss modeling. North American Actuarial Journal, to appear.
Albrecher, H., Bladt, M., & Mueller, A. (2023). Joint lifetime modelling with matrix distributions. Dependence Modeling, 11(1), 1-22.
Bladt, M. & Yslas, J. (2023). Robust claim frequency modeling through phase-type mixture-of-experts regression.Insurance: Mathematics and Economics, 111, 1-22.
matrixdist documentation built on Aug. 8, 2023, 5:06 p.m.
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| matrixdist-package | R Documentation |
Statistics for Matrix Distributions
Description
This package implements tools which are useful for the statistical analysis of discrete, continuous, multivariate, right-censored or regression variants of phase-type distributions. These distributions are absorption times of Markov jump processes, and thus the maximization of their likelihood for statistical estimation is best dealt with using the EM algorithm.
Author(s)
Martin Bladt and Jorge Yslas.
Maintainer: Martin Bladt <martinbladt@gmail.com>
References
Asmussen, S., Nerman, O., & Olsson, M. (1996). Fitting phase-type distributions via the EM algorithm. Scandinavian Journal of Statistics, 23(4),419-441.
Olsson, M. (1996). Estimation of phase-type distributions from censored data. Scandinavian journal of statistics, 24(4), 443-460.
Albrecher, H., & Bladt, M. (2019). Inhomogeneous phase-type distributions and heavy tails. Journal of Applied Probability, 56(4), 1044-1064.
Albrecher, H., Bladt, M., & Yslas, J. (2022). Fitting inhomogeneous Phase-Type distributions to data: The univariate and the multivariate case. Scandinavian Journal of Statistics, 49(1), 44-77
Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2020). Mortality modeling and regression with matrix distributions. Insurance: Mathematics and Economics, 107, 68-87.
Bladt, M., & Yslas, J. (2022). Phase-type mixture-of-experts regression for loss severities. ScandinavianActuarialJournal, 1-27.
Bladt, M. (2022). Phase-type distributions for claim severity regression modeling. ASTIN Bulletin: The journal of the IAA, 52(2), 417-448.
Bladt, M. (2023). A tractable class of Multivariate Phase-type distributions for loss modeling. North American Actuarial Journal, to appear.
Albrecher, H., Bladt, M., & Mueller, A. (2023). Joint lifetime modelling with matrix distributions. Dependence Modeling, 11(1), 1-22.
Bladt, M. & Yslas, J. (2023). Robust claim frequency modeling through phase-type mixture-of-experts regression.Insurance: Mathematics and Economics, 111, 1-22.
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