math.ST · 2026-08-04 · No. 74
Statistics Theory, 2026-08-04.
1 new papers in math.ST. Titles, authors,
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01 — The papers
1 entries-
01
Beyond Modern Asymptotics for Log-Likelihood Ratios in Logistic Regression
Hugo Chardon, Reese Pathak, Nikita Zhivotovskiy
math.ST · cs.IT · cs.LG
We characterize the finite sample behavior of the log-likelihood ratio statistic in binary logistic regression, uniformly over both the design and the target parameter. For $n\geq d\geq 3$, we determine, up to universal constants, its worst case $(1-δ)$ quantile over all fixed collections of design vectors and all target parameters: \[ d\log\left(\frac{e n}{d}\right)+\log\left(\frac{1}δ\right). \] This is a nonasymptotic analogue of the Wilks...
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