5 papers
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…
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…
Bin-Conditional Conformal Prediction of Fatalities from Armed Conflict
David Randahl, Jonathan P. Williams, HÃ¥vard 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…
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…
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…