
Bayesian vs frequentist: comparing Bayesian model selection with a frequentist approach using the iterative smoothing method
On simulated Roman supernova data, Bayesian model selection finds the true model when it is among the candidates, but otherwise only picks the least wrong one. A frequentist test based on iterative smoothing can instead conclude that all tested models are false.
DOI · arXiv:2110.10977Énergie noireSupernovae IaLissage itératifSélection de modèles

