WBCP generalizes BQ-CP to weighted data via a weighted Dirichlet Dir(neff · w̃) that matches frequentist variance, extends stochastic dominance guarantees, and yields O(1/√neff) conditional coverage improvements, demonstrated on spatial prediction.
14): The HPD threshold provides O(1/√neff) improvement in conditional coverage over the marginal rate
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Weighted Bayesian Conformal Prediction
WBCP generalizes BQ-CP to weighted data via a weighted Dirichlet Dir(neff · w̃) that matches frequentist variance, extends stochastic dominance guarantees, and yields O(1/√neff) conditional coverage improvements, demonstrated on spatial prediction.