Skip to content
DraconiticResearch
Search Sources API
194,226 studies31 sourcesUpdated 42 min ago
Peer-reviewedLicence not statedJournal of the American Statistical Association

An Efficient Monte Carlo Method for Valid Prior-Free Possibilistic Statistical Inference

  1. 1Department of Statistics, North Carolina State University

Related

  1. Semiparametrically efficient semi-supervised statistical inference
    Zichun Xu, Daniela Witten, Ali Shojaie
    BiometrikaPeer-reviewedLicence not statedFull text32 citedStatisticsOpenAlex
  2. Second-Order Least Squares Method for Statistical Inference in Linear Models with Asymmetric Errors
    Sanha Kil, Yuliya V. Martsynyuk, Liqun Wang
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
  3. HIFI: A Highly Efficient Framework for Statistical Inference with Foundation Models
    Po-Wei Chen, Shan Yu, Chunlin Li
    arXivPreprintarXiv licenceFull textStatisticsarXiv
  4. Possibilistic Radial Transport for Approximate IM Inference
    Jungeum Kim, Percy Zhai
    arXivPreprintarXiv licenceFull textStatisticsarXiv
  5. Statistical inference and applications of Kumaraswamy Odd Perks power Lomax distribution
    Aleena Thampi, Vasili B. V. Nagarjuna
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textStatisticsCrossref
BibTeX
@article{martin2026efficient,
  title = {{An Efficient Monte Carlo Method for Valid Prior-Free Possibilistic Statistical Inference}},
  author = {Ryan Martin},
  journal = {Journal of the American Statistical Association},
  year = {2026},
  month = may,
  doi = {10.1080/01621459.2026.2671450},
  url = {http://arxiv.org/abs/2501.10585},
}
RIS
TY  - JOUR
TI  - An Efficient Monte Carlo Method for Valid Prior-Free Possibilistic Statistical Inference
AU  - Ryan Martin
PY  - 2026
DA  - 2026/05/13
JO  - Journal of the American Statistical Association
DO  - 10.1080/01621459.2026.2671450
UR  - http://arxiv.org/abs/2501.10585
SN  - 0162-1459
SN  - 1537-274X
ER  -