collaborators

6 papers

stat.AP2026

Model Selection via Focused Information Criteria for Complex Data in Ecology and Evolution

Gerda Claeskens, Céline Cunen, Nils Lid Hjort

Datasets encountered when examining deeper issues in ecology and evolution are often complex. This calls for careful strategies for both model building, model selection, and model…

math.ST2026

Confidence in confidence distributions!

Céline Cunen, Nils Lid Hjort, Tore Schweder

The recent article `Satellite conjunction analysis and the false confidence theorem' (Balch, Martin, and Ferson, 2019, Proceedings of the Royal Society, Series A) points to certain…

stat.ME2026

Combining Information Across Diverse Sources: The II-CC-FF Paradigm

Céline Cunen, Nils Lid Hjort

We introduce and develop a general paradigm for combining information across diverse data sources. In broad terms, suppose is a parameter of interest, built up via components…

stat.ME2026

Optimal inference via confidence distributions for two-by-two tables modelled as Poisson pairs: fixed and random effects

Céline Cunen, Nils Lid Hjort

This paper presents methods for meta-analysis of tables, both with and without allowing heterogeneity in the treatment effects. Meta-analysis is common in medical rese…

stat.ME2026

Confidence Distributions for FIC scores

Céline Cunen, Nils Lid Hjort

When using the Focused Information Criterion (FIC) for assessing and ranking candidate models with respect to how well they do for a given estimation task, it is customary to produ…

stat.AP2025

Combining predictive distributions for time-to-event outcomes in meteorology

Céline Cunen, Thea Roksvåg, Claudio Heinrich-Mertsching +1

Combining forecasts from multiple numerical weather prediction (NWP) models have shown substantial benefit over the use of individual forecast products. Although combination, in a…