Conformal Inference
A distribution-free statistical inference framework that transforms arbitrary scoring functions into valid test statistics (p-values or e-values) via an exchangeability assumption, without requiring parametric assumptions about the data distribution.
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SLICE (Sequential Likelihood-Free Inference via Conformal E-Values) combines conformal inference with e-values to construct exact and anytime-valid confidence sequences for parameters of models with intractable likelihoods.
The validity of conformal inference does not depend on any parametric assumptions about the data distribution, requiring only the exchangeability condition.
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SLICE (Sequential Likelihood-Free Inference via Conformal E-Values) combines conformal inference with e-values to construct exact and anytime-valid confidence sequences for parameters of models with intractable likelihoods.
50%UnverifiedThe validity of conformal inference does not depend on any parametric assumptions about the data distribution, requiring only the exchangeability condition.
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