collaborators

8 papers

stat.ME2026

Conflict Forecasting via Conformal Prediction for Markov Processes

Aditya Basarkar, Emmett B. Kendall, David Randahl +2

Whether or not a country is at war, or experiencing escalating or deescalating levels of conflict, has massive ramifications on a country's national and foreign policy. Given a cou…

stat.AP2026

pintervals: an R package for model-agnostic prediction intervals

David Randahl, Anders Hjort, Jonathan P. Williams

The \pkg{pintervals} package aims to provide a unified framework for constructing prediction intervals and calibrating predictions in a model-agnostic setting using set-aside calib…

stat.ME2024

Forecasting Densities of Fatalities from State-based Conflicts using Observed Markov Models

David Randahl, Johan Vegelius

In this contribution to the VIEWS 2023 prediction challenge, we propose using an observed Markov model for making predictions of densities of fatalities from armed conflicts. The o…

stat.ME2024

This is not normal! (Re-) Evaluating the lower guidelines for regression analysis

David Randahl

The commonly cited rule of thumb for regression analysis, which suggests that a sample size of is sufficient to ensure valid inferences, is frequently referenced but ra…

stat.ME2024

Bin-Conditional Conformal Prediction of Fatalities from Armed Conflict

David Randahl, Jonathan P. Williams, Håvard Hegre

Forecasting armed conflicts is a critical area of research with the potential to save lives and mitigate suffering. While existing forecasting models offer valuable point predictio…

stat.ME2024

When Sensitivity Bias Varies Across Subgroups: The Impact of Non-uniform Polarity in List Experiments

Sophia Hatz, David Randahl

Survey researchers face the problem of sensitivity bias: since people are reluctant to reveal socially undesirable or otherwise risky traits, aggregate estimates of these traits wi…

stat.ME2024

The underreported death toll of wars: a probabilistic reassessment from a structured expert elicitation

Paola Vesco, David Randahl, Håvard Hegre +2

Event datasets including those provided by Uppsala Conflict Data Program (UCDP) are based on reports from the media and international organizations, and are likely to suffer from r…

stat.AP2024

The 2023/24 VIEWS Prediction Challenge: Predicting the Number of Fatalities in Armed Conflict, with Uncertainty

Håvard Hegre, Paola Vesco, Michael Colaresi +37

This draft article outlines a prediction challenge where the target is to forecast the number of fatalities in armed conflicts, in the form of the UCDP `best' estimates, aggregated…