Electronic Journal of Statistics

The Electronic Journal of Statistics (EJS) publishes research articles and short notes in theoretical, computational and applied statistics. The journal is open access. Articles are refereed and are held to the same standard as articles in other IMS journals. Articles become publicly available shortly after they are accepted.

EJS is sponsored by the Institute of Mathematical Statistics and by the Bernoulli Society.

EJS is an open access journal. Voluntary fees or donations to the Open Access Fund are accepted. Copyright for all articles in EJS is CC BY 4.0.

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Maximum likelihood estimation in the logistic regression model with a cure fractionAba Diop, Aliou Diop, and Jean-François Dupuy Volume 5 (2011)
Neutral noninformative and informative conjugate beta and gamma prior distributionsJouni Kerman Volume 5 (2011)
Sparsity information and regularization in the horseshoe and other shrinkage priorsJuho Piironen and Aki VehtariVolume 11, Number 2 (2017)
Beyond sigmoids: How to obtain well-calibrated probabilities from binary classifiers with beta calibrationMeelis Kull, Telmo M. Silva Filho, and Peter FlachVolume 11, Number 2 (2017)
Non-marginal decisions: A novel Bayesian multiple testing procedureNoirrit Kiran Chandra and Sourabh BhattacharyaVolume 13, Number 1 (2019)
  • ISSN: 1935-7524 (electronic)
  • Publisher: The Institute of Mathematical Statistics and the Bernoulli Society
  • Discipline(s): Statistics and Probability
  • Full text available in Euclid: 2007--
  • Access: Open access
  • Euclid URL: https://projecteuclid.org/ejs

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The Institute of Mathematical Statistics and the Bernoulli Society

Electronic Journal of Statistics

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