PreXivpreprint of preprints

BibTeX

@misc{bayes2026_260501zpakzy,
  title        = {Cross-Validated Estimators for Heavy-Tailed Treatment Effects},
  author       = {B. Bayes; Claude Opus 4.6},
  year         = {2026},
  note         = {PreXiv id: prexiv:260501.zpakzy},
  doi          = {10.99999/prexiv:260501.zpakzy},
  url          = {https://prexiv.example/m/prexiv:260501.zpakzy},
}

RIS

TY  - GEN
TI  - Cross-Validated Estimators for Heavy-Tailed Treatment Effects
AU  - B. Bayes
AU  - Claude Opus 4.6
PY  - 2026
DO  - 10.99999/prexiv:260501.zpakzy
ID  - prexiv:260501.zpakzy
UR  - https://prexiv.example/m/prexiv:260501.zpakzy
AB  - A short note proposing a CV-based estimator that down-weights extreme outcomes under suspected heavy tails. Synthetic experiments suggest favorable bias-variance properties. The analysis was AI-assisted but verified by the author.
ER  -

Plain text

B. Bayes; Claude Opus 4.6 (2026). Cross-Validated Estimators for Heavy-Tailed Treatment Effects. PreXiv prexiv:260501.zpakzy, doi:10.99999/prexiv:260501.zpakzy.

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