9 papers
Statistics of multivariate extremes under random censoring
Martin Bladt
We study tail dependence of a -dimensional random vector whose coordinates are subject to random right censoring. Along each fixed direction the censored problem reduces exactly…
Censored Heteroscedastic Extremes
Martin Bladt, Theodor Henningsen
We study estimation of tail heterogeneity for non-identically distributed extreme observations subject to random right-censoring. In the uncensored setting, such heterogeneity is d…
Payment Process Estimation in Aggregated Insurance Models
Martin Bladt, Marcus Christiansen
Insurance payments may depend on latent micro states although only macro states and realized payments are observed. We study a sojourn-payment model for such aggregated multi-state…
Scoring Rules with Normalized Upper Order Statistics for Tail Inference
Martin Bladt, Christoffer Øhlenschlæger
This paper proposes a scoring-rule-based method for ranking predictive distributions in the Fréchet domain that is able to distinguish between different tail indices. The approach…
Nonparametric Survival Estimation with Contaminated and Adjudicated Events
Martin Bladt, Kristian Vilhelm Dinesen
We study the conditional expert Kaplan-Meier estimator, an extension of the classical Kaplan--Meier estimator designed for time-to-event data subject to both right-censoring and co…
Consistency of Honest Decision Trees and Random Forests
Martin Bladt, Rasmus Frigaard Lemvig
We study various types of consistency of honest decision trees and random forests in the regression setting. In contrast to related literature, our proofs are elementary and follow…
Bayesian non-parametric survival estimation: stochastic hyperparameter sequences and distribution splicing
Martin Bladt, Jorge González Cázares
A Bayesian non-parametric framework for studying time-to-event data is proposed, where the prior distribution is allowed to depend on an additional random source, and may update wi…
Conditional Extreme Value Estimation for Dependent Time Series
Martin Bladt, Laurits Glargaard, Theodor Henningsen
We study the consistency and weak convergence of the conditional tail function and conditional Hill estimators under broad dependence assumptions for a heavy-tailed response sequen…
Estimating absorption time distributions of general Markov jump processes
Jamaal Ahmad, Martin Bladt, Mogens Bladt
The estimation of absorption time distributions of Markov jump processes is an important task in various branches of statistics and applied probability. While the time-homogeneous…