64 citations · 130 across the 26 of their papers we have counts for
26 papers
Approximating Bayesian leave-one-group-out cross-validation
Anna Elisabeth Riha, Svenja Jedhoff, Paul-Christian Bürkner +1
When data are grouped, hierarchical or multilevel models are commonly used to account for group-level variation with group-specific parameters. Leave-one-group-out cross-validation…
To select or not to select: predictively consistent priors instead of model selection
Anna Elisabeth Riha, Leevi Lindgren, David Kohns +2
Bayesian modelling workflows often consider multiple candidate models of varying complexity. Model selection is commonly used to navigate potential trade-offs between model complex…
LOO-PIT predictive model checking
Herman Tesso, Aki Vehtari
We consider predictive checking for Bayesian model assessment using leave-one-out probability integral transform (LOO-PIT). LOO-PIT values are conditional cumulative predictive pro…
Predictive Assessment and Comparison of Bayesian Survival Models for Cancer Recurrence
Saku Suorsa, Aki Vehtari
Complex data features, such as unmodelled censored event times and variables with time-dependent effects, are common in cancer recurrence studies and pose challenges for Bayesian s…
Efficient scenario analysis in real-time Bayesian election forecasting via sequential meta-posterior sampling
Geonhee Han, Andrew Gelman, Aki Vehtari
Bayesian aggregation lets election forecasters combine diverse sources of information, such as state polls and economic and political indicators: as in our collaboration with The E…
Bridge Sampling Diagnostics
Giorgio Micaletto, Aki Vehtari
In Bayesian statistics, the marginal likelihood is used for model selection and averaging, yet it is often challenging to compute accurately for complex models. Approaches such as…