12 papers
Cure models: from mixture to matrix distributions
Martin Bladt, Jorge Yslas
Cure rate models address survival data in which a proportion of individuals will never experience the event of interest. Existing parametric approaches are predominantly based on f…
Assessing continuous common-shock risk through matrix distributions
Martin Bladt, Oscar Peralta, Jorge Yslas
We introduce a class of continuous-time bivariate phase-type distributions for modeling dependencies from common shocks. The construction uses continuous-time Markov processes that…
Bivariate phase-type distributions for experience rating in disability insurance
Christian Furrer, Jacob Juhl Sørensen, Jorge Yslas
In this paper, we consider the problem of experience rating within the classic Markov chain life insurance framework. We begin by establishing a link between mixed Poisson distribu…
Phase-type mixture-of-experts regression for loss severities
Martin Bladt, Jorge Yslas
The task of modeling claim severities is addressed when data is not consistent with the classical regression assumptions. This framework is common in several lines of business with…
Heavy-tailed phase-type distributions: A unified approach
Martin Bladt, Jorge Yslas
A phase-type distribution is the distribution of the time until absorption in a finite state-space time-homogeneous Markov jump process, with one absorbing state and the rest being…
Phase-type frailty models: A flexible approach to modeling unobserved heterogeneity in survival analysis
Jorge Yslas
Frailty models are essential tools in survival analysis for addressing unobserved heterogeneity and random effects in the data. These models incorporate a random effect, the frailt…
Continuous scaled phase-type distributions
Hansjoerg Albrecher, Martin Bladt, Mogens Bladt +1
Products between phase-type distributed random variables and any independent, positive and continuous random variable are studied. Their asymptotic properties are established, and…
matrixdist: An R Package for Statistical Analysis of Matrix Distributions
Martin Bladt, Alaric Mueller, Jorge Yslas
The matrixdist R package provides a comprehensive suite of tools for the statistical analysis of matrix distributions, including phase-type, inhomogeneous phase-type, discrete phas…
Mortality modeling and regression with matrix distributions
Hansjoerg Albrecher, Martin Bladt, Mogens Bladt +1
In this paper we investigate the flexibility of matrix distributions for the modeling of mortality. Starting from a simple Gompertz law, we show how the introduction of matrix-valu…
Fitting inhomogeneous phase-type distributions to data: the univariate and the multivariate case
Hansjoerg Albrecher, Mogens Bladt, Jorge Yslas
The class of inhomogeneous phase-type distributions (IPH) was recently introduced in Albrecher and Bladt (2019) as an extension of the classical phase-type (PH) distributions. Like…
Point process convergence for the off-diagonal entries of sample covariance matrices
Johannes Heiny, Thomas Mikosch, Jorge Yslas
We study point process convergence for sequences of iid random walks. The objective is to derive asymptotic theory for the extremes of these random walks. We show convergence of th…
Gumbel and Fréchet convergence of the maxima of independent random walks
Thomas Mikosch, Jorge Yslas
We consider point process convergence for sequences of iid random walks. The objective is to derive asymptotic theory for the largest extremes of these random walks. We show conver…