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.

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

Top downloads over the last seven days

Asymptotic properties of quasi-maximum likelihood estimators in observation-driven time series modelsRandal Douc, Konstantinos Fokianos, and Eric MoulinesVolume 11, Number 2 (2017)
Converting high-dimensional regression to high-dimensional conditional density estimationRafael Izbicki and Ann B. LeeVolume 11, Number 2 (2017)
A Wald-type test statistic for testing linear hypothesis in logistic regression models based on minimum density power divergence estimatorAyanendranath Basu, Abhik Ghosh, Abhijit Mandal, Nirian Martín, and Leandro PardoVolume 11, Number 2 (2017)
Regularized k-means clustering of high-dimensional data and its asymptotic consistencyWei Sun, Junhui Wang, and Yixin Fang Volume 6 (2012)
Parametrically guided local quasi-likelihood with censored dataMajda Talamakrouni, Anouar El Ghouch, and Ingrid Van KeilegomVolume 11, Number 2 (2017)
  • 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: http://projecteuclid.org/ejs