arXiv (All)
open access
Improved E-Value Thresholds with Applications to Multiple and Sequential Testing
E-values provide a flexible framework for statistical inference, but the universal threshold $1/α$ can be conservative when the null distribution has additional structure. We study how structural restrictions limit the worst-case concentration underlying Markov's inequality, using a nondecreasing de
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- A dimension-free comparison between expectation thresholds and fractional expectation thresholds#1084614
- Dobrushin Coefficients of Private Mechanisms Beyond Local Differential Privacy#1355960
- Beyond Zipf's Law: Equifinality and Mechanistic Inference from Scaling Laws#620436
- Beyond Zipf's Law: Equifinality and Mechanistic Inference from Scaling Laws#618757
- Bayesian Evidence Test for Precise Hypotheses#770612
Record · ID 1248113
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive