collaborators

7 papers

math.ST2026

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…

stat.ME2026

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…

stat.ME2026

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…

stat.ME2026

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…

math.ST2026

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…

stat.ME2026

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…