6 papers · 1 filter
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…
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…
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…
The underreported death toll of wars: a probabilistic reassessment from a structured expert elicitation
Paola Vesco, David Randahl, HÃ¥vard 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…