Rao-Blackwellized e-variables

Summary We show that for any concave utility, the expected utility of an e-variable can only increase after conditioning on a sufficient statistic, echoing the classic Rao-Blackwell theorem. The simplest form of the result has a straightforward proof using Jensen’s inequality, but we prove more sophisticated versions. We provide several applications of this insight, including a derivation of the log-optimal e-variable for testing the variance in a linear regression model.

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Publication Details

Journal
Biometrika
Published
2026-10-15
DOI
https://doi.org/10.1093/biomet/asag061
Primary Topic
Statistical Methods and Inference
Type
article
Field-Weighted Citation Impact
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article

Rao-Blackwellized e-variables

Biometrika
Statistical Methods and Inference
article

Rao-Blackwellized e-variables

article en

Abstract

Summary We show that for any concave utility, the expected utility of an e-variable can only increase after conditioning on a sufficient statistic, echoing the classic Rao-Blackwell theorem. The simplest form of the result has a straightforward proof using Jensen’s inequality, but we prove more sophisticated versions. We provide several applications of this insight, including a derivation of the log-optimal e-variable for testing the variance in a linear regression model.

Biometrika
Centrum Wiskunde & Informatica (NL), Carnegie Mellon University (US), Stanford University (US)
Openalex Percentile: Top 95%
Statistical Methods and Inference
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