8 citations · 14 across the 28 of their papers we have counts for
37 papers
Survival Isotonic Distributional Regression
Martin Bladt, Alexander Henzi, Bram van den Heuvel +1
We introduce Survival-IDR (S-IDR), a nonparametric estimator of conditional survival distributions under order restrictions, extending Isotonic Distributional Regression (IDR; Henz…
Local estimation of transition rates of jump processes through discretization
Martin Bladt, Rasmus Frigaard Lemvig
We investigate the Poisson regression method for Markov and semi-Markov jump processes from a nonparametric angle, allowing the lengths of the time and duration intervals in the pa…
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…
Non-parametric cure models through extreme-value tail estimation
Jan Beirlant, Martin Bladt, Ingrid Van Keilegom
In survival analysis, the estimation of the proportion of subjects who will never experience the event of interest, termed the cure rate, has received considerable attention recent…
Modeling discrete common-shock risks through matrix distributions
Martin Bladt, Eric C. K. Cheung, Oscar Peralta +1
We introduce a novel class of bivariate common-shock discrete phase-type (CDPH) distributions to describe dependencies in loss modeling, with an emphasis on those induced by common…
Censored and extreme losses: functional convergence and applications to tail goodness-of-fit
Martin Bladt, Christoffer Øhlenschlæger
This paper establishes the functional convergence of the Extreme Nelson--Aalen and Extreme Kaplan--Meier estimators, which are designed to capture the heavy-tailed behaviour of cen…
Uniform Consistency of Generalized Fréchet Means
Andrea Aveni, Martin Bladt, Sayan Mukherjee
Loss-based notions of centre on nonlinear spaces range from the Fréchet mean and power means to the geometric median and, in a limiting sense, the Chebyshev centre. To use such sum…
Heterogeneous extremes in the presence of random covariates and censoring
Martin Bladt, Christoffer Øhlenschlæger
The task of analyzing extreme events with censoring effects is considered under a framework allowing for random covariate information. A wide class of estimators that can be cast a…
Extremile scalar-on-function regression
Maria Laura Battagliola, Martin Bladt
Extremiles provide a generalization of quantiles which are not only robust, but also have an intrinsic link with extreme value theory. This paper introduces an extremile regression…
Censored extreme value estimation
Martin Bladt, Igor Rodionov
A novel and comprehensive methodology designed to tackle the challenges posed by extreme values in the context of random censorship is introduced. The main focus is on the analysis…
Approximations of semi-Markov processes and insurance policy valuation
Martin Bladt, Andreea Minca, Oscar Peralta
Inspired by a duration-dependent life insurance model, we consider continuous-time semi-Markov jump processes, initially assumed to have a finite state-space. We develop approximat…
Individual claims reserving using the Aalen--Johansen estimator
Martin Bladt, Gabriele Pittarello
We propose an individual claims reserving model based on the conditional Aalen-Johansen estimator, as developed in Bladt and Furrer (2023b). In our approach, we formulate a multi-s…
Conditional Aalen--Johansen estimation
Martin Bladt, Christian Furrer
The conditional Aalen--Johansen estimator, a general-purpose non-parametric estimator of conditional state occupation probabilities, is introduced. The estimator is applicable for…
Joint discrete and continuous matrix distribution modelling
Martin Bladt, Clara Brimnes Gardner
In this paper we introduce a bivariate distribution on arising from a single underlying Markov jump process. The marginal distributions are phase…
Expert Kaplan--Meier estimation
Martin Bladt, Christian Furrer
The setting of a right-censored random sample subject to contamination is considered. In various fields, expert information is often available and used to overcome the contaminatio…
Informed censoring: the parametric combination of data and expert information
Hansjörg Albrecher, Martin Bladt
The statistical censoring setup is extended to the situation when random measures can be assigned to the realization of datapoints, leading to a new way of incorporating expert inf…
Strongly convergent homogeneous approximations to inhomogeneous Markov jump processes and applications
Martin Bladt, Oscar Peralta
The study of time-inhomogeneous Markov jump processes is a traditional topic within probability theory that has recently attracted substantial attention in various applications. Ho…
Phase-type distributions for claim severity regression modeling
Martin Bladt
This paper addresses the task of modeling severity losses using segmentation when the data distribution does not fall into the usual regression frameworks. This situation is not un…
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…
Fractional Inhomogeneous Multi-state Models in Life Insurance
Martin Bladt
In this paper, we demonstrate through the use of matrix calculus a transparent analysis of fractional inhomogeneous Markov models for life insurance where transition matrices commu…
A tractable class of multivariate phase-type distributions for loss modeling
Martin Bladt
Phase-type (PH) distributions are a popular tool for the analysis of univariate risks in numerous actuarial applications. Their multivariate counterparts (MPH), however, hav…
Time series models with infinite-order partial copula dependence
Martin Bladt, Alexander J. McNeil
Stationary and ergodic time series can be constructed using an s-vine decomposition based on sets of bivariate copula functions. The extension of such processes to infinite copula…
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…