3 citations · 3 across the 3 of their papers we have counts for
4 papers
Joint estimation of the predictive ability of experts using a multi-output Gaussian process
Oscar Oelrich, Mattias Villani
A multi-output Gaussian process (GP) is introduced as a model for the joint posterior distribution of the local predictive ability of set of models and/or experts, conditional on a…
Modeling local predictive ability using power-transformed Gaussian processes
Oscar Oelrich, Mattias Villani
A Gaussian process is proposed as a model for the posterior distribution of the local predictive ability of a model or expert, conditional on a vector of covariates, from historica…
Local Prediction Pools
Oscar Oelrich, Mattias Villani, Sebastian Ankargren
We propose local prediction pools as a method for combining the predictive distributions of a set of experts conditional on a set of variables believed to be related to the predict…
When are Bayesian model probabilities overconfident?
Oscar Oelrich, Shutong Ding, Måns Magnusson +2
Bayesian model comparison is often based on the posterior distribution over the set of compared models. This distribution is often observed to concentrate on a single model even wh…