References in zbMATH (referenced in 11 articles , 1 standard article )

Showing results 1 to 11 of 11.
Sorted by year (citations)

  1. Banerjee, Trambak; Liu, Qiang; Mukherjee, Gourab; Sun, Wengunag: A general framework for empirical Bayes estimation in discrete linear exponential family (2021)
  2. Xing, Zhengrong; Carbonetto, Peter; Stephens, Matthew: Flexible signal denoising via flexible empirical Bayes shrinkage (2021)
  3. Jiang, Wenhua: On general maximum likelihood empirical Bayes estimation of heteroscedastic IID normal means (2020)
  4. Koenker, Roger; Gu, Jiaying: Comment: Minimalist (g)-modeling (2019)
  5. Feng, Long; Dicker, Lee H.: Approximate nonparametric maximum likelihood for mixture models: a convex optimization approach to fitting arbitrary multivariate mixing distributions (2018)
  6. Madrid-Padilla, Oscar-Hernan; Polson, Nicholas G.; Scott, James: A deconvolution path for mixtures (2018)
  7. Youngseok Kim, Peter Carbonetto, Matthew Stephens, Mihai Anitescu: A Fast Algorithm for Maximum Likelihood Estimation of Mixture Proportions Using Sequential Quadratic Programming (2018) arXiv
  8. Roger Koenker; Jiaying Gu: REBayes: An R Package for Empirical Bayes Mixture Methods (2017) not zbMATH
  9. Zhao, Sihai Dave: Integrative genetic risk prediction using non-parametric empirical Bayes classification (2017)
  10. Koenker, Roger; Mizera, Ivan: Convex optimization, shape constraints, compound decisions, and empirical Bayes rules (2014)
  11. Roger Koenker and Ivan Mizera: Convex Optimization in R (2014) not zbMATH