scout

scout: Implements the Scout method for Covariance-Regularized Regression. Implements the Scout method for regression, described in ”Covariance-regularized regression and classification for high-dimensional problems”, by Witten and Tibshirani (2008), Journal of the Royal Statistical Society, Series B 71(3): 615-636.


References in zbMATH (referenced in 17 articles , 1 standard article )

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  1. Aste, Tomaso; Di Matteo, T.: Sparse causality network retrieval from short time series (2017)
  2. Treister, Eran; Turek, Javier S.; Yavneh, Irad: A multilevel framework for sparse optimization with application to inverse covariance estimation and logistic regression (2016)
  3. Martella, Francesca; Vicari, Donatella; Vichi, Maurizio: Partitioning predictors in multivariate regression models (2015)
  4. El Anbari, Mohammed; Mkhadri, Abdallah: Penalized regression combining the $ L_1$ norm and a correlation based penalty (2014)
  5. Paul, Debashis; Aue, Alexander: Random matrix theory in statistics: a review (2014)
  6. Rothman, Adam J.; Forzani, Liliana: On the existence of the weighted bridge penalized Gaussian likelihood precision matrix estimator (2014)
  7. Wang, Y.; Daniels, M.J.: Computationally efficient banding of large covariance matrices for ordered data and connections to banding the inverse Cholesky factor (2014)
  8. Boonstra, Philip S.; Mukherjee, Bhramar; Taylor, Jeremy M.G.: Bayesian shrinkage methods for partially observed data with many predictors (2013)
  9. Cook, R.Dennis; Forzani, Liliana; Rothman, Adam J.: Prediction in abundant high-dimensional linear regression (2013)
  10. Hardin, Johanna; Garcia, Stephan Ramon; Golan, David: A method for generating realistic correlation matrices (2013)
  11. Cook, R.Dennis; Forzani, Liliana; Rothman, Adam J.: Estimating sufficient reductions of the predictors in abundant high-dimensional regressions (2012)
  12. Li, Ran; Wu, Baolin: Sparse regularized discriminant analysis with application to microarrays (2012)
  13. Städler, Nicolas; Bühlmann, Peter: Missing values: sparse inverse covariance estimation and an extension to sparse regression (2012)
  14. Pourahmadi, Mohsen: Covariance estimation: the GLM and regularization perspectives (2011)
  15. Ahdesmäki, Miika; Strimmer, Korbinian: Feature selection in omics prediction problems using cat scores and false nondiscovery rate control (2010)
  16. Allen, Genevera I.; Tibshirani, Robert: Transposable regularized covariance models with an application to missing data imputation (2010)
  17. Witten, Daniela M.; Tibshirani, Robert: Covariance-regularized regression and classification for high dimensional problems (2009)