Universal Inference adapted via edge sampling yields e-values for finite-sample model selection and hypothesis testing on dependent network data, with proofs of validity and power under alternatives.
ThenE(logE n) =−∞
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Universal Inference for model selection on networks
Universal Inference adapted via edge sampling yields e-values for finite-sample model selection and hypothesis testing on dependent network data, with proofs of validity and power under alternatives.