Skip to content
DraconiticResearch
Search Sources API
201,818 studies31 sourcesUpdated 35 min ago
PreprintarXiv licencearXiv

Moment-Orthogonal Quadratic-Envelope E-Processes for Anytime-Valid Location Inference

Abstract

E-process confidence sequences for unbounded means typically use a variance bound and a first-order score, leaving skewness and kurtosis unused. We construct a quadratic-envelope e-process from a conditionally centered vector score with a predictable second-moment bound. Under moment information specified independently of the tested stream, it stays positive on unbounded support and gives exact anytime-valid coverage under predictable strategies and fixed mixtures, without score clipping. For a location family with known central moments through order four, the centered observation and its centered square yield an exact confidence sequence whose local width shrinks, relative to a first-order construction, by a factor determined by skewness and kurtosis. At level 5%, the largest null ever-crossing rate was 4.63%; on two zero-inflated-lognormal families median stopping times fell by 36.8-45.8%. When the moments are calibrated on an independent reference sample, a centering-robust factor keeps exact coverage at a closed-form width cost: the median gain was 21.6-30.3% for Gamma(2) and lognormal errors with 10^6 reference observations, and a loss of up to 9.9% with 10^4. On public Fermi gamma-ray detector data with a declared stability margin, it crossed at the current location in 1.8% of 225 windows and stopped 30-35% earlier than the calibrated first-order method.

Related

  1. Computing the convex envelope of bivariate piecewise linear-quadratic functions in linear time
    Tanmaya Karmarkar, Yves Lucet
    arXivPreprintCC BY 4.0Full textOptimisation & controlarXiv
  2. A Gamma envelope and sharp moment inequalities for Gaussian quadratic forms
    Zhekai Pang
    arXivPreprintCC BY-NC-SA 4.0Full textProbabilityStatisticsarXiv
  3. One Inference, Four Failure Modes: Formal Models of Why Pain Location Fails
    Adam Y. Shavit
    arXivPreprintCC BY-NC-ND 4.0Full textNeuroscienceStatisticsarXiv
  4. Orthogonal Inference for Conditional Z-Estimation without Cross-Fitting: A Distributional Nearest-Neighbor Approach
    Jakob R. Juergens
    arXivPreprintarXiv licenceFull textStatisticsarXiv
  5. Quadratic variations of rough generalized Hermite processes: hidden long memory and a universal Gaussian boundary field
    Obayda Julien Assaad
    arXivPreprintarXiv licenceFull textProbabilityarXiv
BibTeX
@misc{zabolotnii2026momentorthogonal,
  title = {{Moment-Orthogonal Quadratic-Envelope E-Processes for Anytime-Valid Location Inference}},
  author = {Serhii Zabolotnii},
  howpublished = {arXiv},
  year = {2026},
  month = nov,
  doi = {10.48550/arxiv.2611.01637},
  eprint = {2611.01637},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2611.01637},
}
RIS
TY  - UNPB
TI  - Moment-Orthogonal Quadratic-Envelope E-Processes for Anytime-Valid Location Inference
AU  - Serhii Zabolotnii
PY  - 2026
DA  - 2026/11/01
PB  - arXiv
DO  - 10.48550/arxiv.2611.01637
UR  - https://arxiv.org/abs/2611.01637
AB  - E-process confidence sequences for unbounded means typically use a variance bound and a first-order score, leaving skewness and kurtosis unused. We construct a quadratic-envelope e-process from a conditionally centered vector score with a predictable second-moment bound. Under moment information specified independently of the tested stream, it stays positive on unbounded support and gives exact anytime-valid coverage under predictable strategies and fixed mixtures, without score clipping. For a location family with known central moments through order four, the centered observation and its centered square yield an exact confidence sequence whose local width shrinks, relative to a first-order construction, by a factor determined by skewness and kurtosis. At level 5%, the largest null ever-crossing rate was 4.63%; on two zero-inflated-lognormal families median stopping times fell by 36.8-45.8%. When the moments are calibrated on an independent reference sample, a centering-robust factor keeps exact coverage at a closed-form width cost: the median gain was 21.6-30.3% for Gamma(2) and lognormal errors with 10^6 reference observations, and a loss of up to 9.9% with 10^4. On public Fermi gamma-ray detector data with a declared stability margin, it crossed at the current location in 1.8% of 225 windows and stopped 30-35% earlier than the calibrated first-order method.
ER  -