References in zbMATH (referenced in 45 articles )

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  1. Cohen, Arthur; Kolassa, John; Sackrowitz, Harold B.: Penalized likelihood and multiple testing (2019)
  2. Barber, Rina Foygel; Kolar, Mladen: ROCKET: robust confidence intervals via Kendall’s tau for transelliptical graphical models (2018)
  3. Caner, Mehmet; Kock, Anders Bredahl: Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso (2018)
  4. Gong, Siliang; Zhang, Kai; Liu, Yufeng: Efficient test-based variable selection for high-dimensional linear models (2018)
  5. Holmes, Susan: Statistical proof? The problem of irreproducibility (2018)
  6. Hyun, Sangwon; G’sell, Max; Tibshirani, Ryan J.: Exact post-selection inference for the generalized lasso path (2018)
  7. Javanmard, Adel; Montanari, Andrea: Debiasing the Lasso: optimal sample size for Gaussian designs (2018)
  8. Javanmard, Adel; Montanari, Andrea: Online rules for control of false discovery rate and false discovery exceedance (2018)
  9. Liu, Yaowu; Xie, Jun: Powerful test based on conditional effects for genome-wide screening (2018)
  10. Mousavi, Ali; Maleki, Arian; Baraniuk, Richard G.: Consistent parameter estimation for Lasso and approximate message passing (2018)
  11. Neykov, Matey; Ning, Yang; Liu, Jun S.; Liu, Han: A unified theory of confidence regions and testing for high-dimensional estimating equations (2018)
  12. Shah, Rajen D.; Bühlmann, Peter: Goodness-of-fit tests for high dimensional linear models (2018)
  13. Tian, Xiaoying; Taylor, Jonathan: Selective inference with a randomized response (2018)
  14. Tibshirani, Ryan J.; Rinaldo, Alessandro; Tibshirani, Rob; Wasserman, Larry: Uniform asymptotic inference and the bootstrap after model selection (2018)
  15. Yang, Zhuoran; Ning, Yang; Liu, Han: On semiparametric exponential family graphical models (2018)
  16. Bécu, Jean-Michel; Grandvalet, Yves; Ambroise, Christophe; Dalmasso, Cyril: Beyond support in two-stage variable selection (2017)
  17. Bertsimas, Dimitris; King, Angela: Logistic regression: from art to science (2017)
  18. Grogan, Tristan R.; Elashoff, David A.: A simulation based method for assessing the statistical significance of logistic regression models after common variable selection procedures (2017)
  19. Groll, Andreas; Tutz, Gerhard: Variable selection in discrete survival models including heterogeneity (2017)
  20. Maciak, Matúš: Testing shape constraints in Lasso regularized joinpoint regression (2017)

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