A location-invariant estimator of extremal quantile treatment effects for heavy-tailed distributions
Paper recorded by Signals 4 on 2026-09-03 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-03 on arXiv · recorded by Signals 4 on 2026-09-04
Category: cs.LG · 机器学习 · first seen 2026-09-04
Abstract
Quantile treatment effects (QTEs) measure the effect of a treatment on the distribution of an outcome, and their estimation at extreme quantile levels is of central interest in applications where the target quantiles lie far beyond the range of the data. For heavy-tailed potential outcomes, existing extremal QTE estimators rely on extrapolation combined with a causal extreme value index (EVI) esti
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Cite this page: A location-invariant estimator of extremal quantile treatment effects for heavy-tailed distributions: the #139 most recent of 215 cs.LG papers we have recorded (as of 2026-09-03). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/a-location-invariant-estimator-of-extremal-quantile-treatment-effects-for-heavy-.html
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