stat.ME · 2026-08-21 · No. 91

Methodology, 2026-08-21.

3 new papers in stat.ME. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

3 entries
  1. 01

    Multi-Method Causal Evidence Synthesis: Ranking Candidate Drivers by Convergent Cross-Method Evidence from Observational Data

    Manish Gupta, Dipanjan De

    stat.ME · cs.AI

    Practitioners inferring causality from observational data usually rely on a single method and treat its output as causal truth. Recent tools select an optimal method for a dataset, and recent ensembles aggregate multiple causal-discovery algorithms into one graph, but little work pools evidence across different mathematical traditions, including non-causal ones. We present Multi-Method Causal Evidence Synthesis (MCES), a framework that ranks...

    arxiv.org/abs/2608.20187 · PDF

  2. 02

    Where Does the Union Bound Go? Best-Arm Identification and Strong FWER Control

    Rianne de Heide

    stat.ME · cs.LG · stat.ML

    In fixed-confidence best-arm identification, proofs often use a union bound across the competing arms. From a multiple-testing point of view this can look puzzling: if the best arm is unique, only one hypothesis of the form ``arm $i$ is best'' can be true. Why then should there be a Bonferroni-type factor of $K-1$? The answer is that there are two natural ways to orient the hypotheses. In one orientation, best-arm identification is literally...

    arxiv.org/abs/2608.19903 · PDF

  3. 03

    A Repeated Measurements Approach to $SoH$ Battery Modelling of Cyclic Aged Data in a Laboratory Environment

    Mark Cary, Charles Bokor

    stat.ME · cs.LG · eess.SY

    This document describes the application of a first order linearised nonlinear repeated measurements approach to the analysis of battery cell ageing profiles generated under controlled conditions in a laboratory. The primary advantage of the model is it reflects the obvious structure in the data. Consequently, it is a two-component of variance model: variation within ageing profiles (measurement noise) and variation among ageing profiles...

    arxiv.org/abs/2608.19879 · PDF

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