hierNet: A Lasso for Hierarchical Interactions. Fits sparse interaction models for continuous and binary responses subject to the strong (or weak) hierarchy restriction that an interaction between two variables only be included if both (or at least one of) the variables is included as a main effect. For more details, see Bien, J., Taylor, J., Tibshirani, R., (2013) ”A Lasso for Hierarchical Interactions.” Annals of Statistics. 41(3). 1111-1141.

References in zbMATH (referenced in 27 articles )

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  1. Dong, Hongbo; Ahn, Miju; Pang, Jong-Shi: Structural properties of affine sparsity constraints (2019)
  2. Lederer, Johannes; Yu, Lu; Gaynanova, Irina: Oracle inequalities for high-dimensional prediction (2019)
  3. Li, Yang; Liu, Jun S.: Robust variable and interaction selection for logistic regression and general index models (2019)
  4. Mak, Simon; Wu, C. F. Jeff: \textsfcmenet: A new method for bi-level variable selection of conditional main effects (2019)
  5. Sato, Toshiki; Takano, Yuichi; Nakahara, Takanobu: Investigating consumers’ store-choice behavior via hierarchical variable selection (2019)
  6. Tyagi, Hemant; Vybiral, Jan: Learning general sparse additive models from point queries in high dimensions (2019)
  7. Daniel, Jeffrey; Horrocks, Julie; Umphrey, Gary J.: Penalized composite likelihoods for inhomogeneous Gibbs point process models (2018)
  8. Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter: Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting (2018)
  9. Dong, Yao; Jiang, He: A two-stage regularization method for variable selection and forecasting in high-order interaction model (2018)
  10. Hao, Ning; Feng, Yang; Zhang, Hao Helen: Model selection for high-dimensional quadratic regression via regularization (2018)
  11. Kim, Joungyoun; Lim, Johan; Kim, Yongdai; Jang, Woncheol: Bayesian variable selection with strong heredity constraints (2018)
  12. She, Yiyuan; Wang, Zhifeng; Jiang, He: Group regularized estimation under structural hierarchy (2018)
  13. Thanei, Gian-Andrea; Meinshausen, Nicolai; Shah, Rajen D.: The (xyz) algorithm for fast interaction search in high-dimensional data (2018)
  14. Ternès, Nils; Rotolo, Federico; Heinze, Georg; Michiels, Stefan: Identification of biomarker-by-treatment interactions in randomized clinical trials with survival outcomes and high-dimensional spaces (2017)
  15. Gross, Samuel M.; Tibshirani, Robert: Data shared lasso: a novel tool to discover uplift (2016)
  16. He, Yawei; Chen, Zehua: The EBIC and a sequential procedure for feature selection in interactive linear models with high-dimensional data (2016)
  17. Ustun, Berk; Rudin, Cynthia: Supersparse linear integer models for optimized medical scoring systems (2016)
  18. Zhao, Junlong; Leng, Chenlei: An analysis of penalized interaction models (2016)
  19. Ziel, Florian: Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR-ARCH type processes (2016)
  20. Bien, Jacob; Simon, Noah; Tibshirani, Robert: Convex hierarchical testing of interactions (2015)

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