References in zbMATH (referenced in 26 articles , 1 standard article )

Showing results 1 to 20 of 26.
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  1. Posch, Konstantin; Arbeiter, Maximilian; Pilz, Juergen: A novel Bayesian approach for variable selection in linear regression models (2020)
  2. De Wiel, Mark A. van; Te Beest, Dennis E.; Münch, Magnus M.: Learning from a lot: empirical Bayes for high-dimensional model-based prediction (2019)
  3. Gan, Lingrui; Narisetty, Naveen N.; Liang, Feng: Bayesian regularization for graphical models with unequal shrinkage (2019)
  4. Gutiérrez, Luis; Barrientos, Andrés F.; González, Jorge; Taylor-Rodríguez, Daniel: A Bayesian nonparametric multiple testing procedure for comparing several treatments against a control (2019)
  5. Moran, Gemma E.; Ročková, Veronika; George, Edward I.: Variance prior forms for high-dimensional Bayesian variable selection (2019)
  6. Narisetty, Naveen N.; Shen, Juan; He, Xuming: Skinny Gibbs: a consistent and scalable Gibbs sampler for model selection (2019)
  7. Ning, Bo; Ghosal, Subhashis; Thomas, Jewell: Bayesian method for causal inference in spatially-correlated multivariate time series (2019)
  8. Ni, Yang; Stingo, Francesco C.; Baladandayuthapani, Veerabhadran: Bayesian graphical regression (2019)
  9. Zhang, Chun-Xia; Xu, Shuang; Zhang, Jiang-She: A novel variational Bayesian method for variable selection in logistic regression models (2019)
  10. Consonni, Guido; Fouskakis, Dimitris; Liseo, Brunero; Ntzoufras, Ioannis: Prior distributions for objective Bayesian analysis (2018)
  11. Du, Xingqi; Ghosal, Subhashis: Bayesian discriminant analysis using a high dimensional predictor (2018)
  12. Fouskakis, Dimitris; Ntzoufras, Ioannis; Perrakis, Konstantinos: Power-expected-posterior priors for generalized linear models (2018)
  13. Linero, Antonio R.: Bayesian regression trees for high-dimensional prediction and variable selection (2018)
  14. Miranda, Michelle F.; Zhu, Hongtu; Ibrahim, Joseph G.: TPRM: tensor partition regression models with applications in imaging biomarker detection (2018)
  15. Ročková, Veronika: Bayesian estimation of sparse signals with a continuous spike-and-slab prior (2018)
  16. Ročková, Veronika: Particle EM for variable selection (2018)
  17. Ročková, Veronika; George, Edward I.: The spike-and-slab LASSO (2018)
  18. Yu, Cheng-Han; Prado, Raquel; Ombao, Hernando; Rowe, Daniel: A Bayesian variable selection approach yields improved detection of brain activation from complex-valued fMRI (2018)
  19. Latouche, Pierre; Mattei, Pierre-Alexandre; Bouveyron, Charles; Chiquet, Julien: Combining a relaxed EM algorithm with Occam’s razor for Bayesian variable selection in high-dimensional regression (2016)
  20. Zhao, Kaifeng; Lian, Heng: The expectation-maximization approach for Bayesian quantile regression (2016)

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