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 13 articles , 1 standard article )

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  1. Martella, Francesca; Vicari, Donatella; Vichi, Maurizio: Partitioning predictors in multivariate regression models (2015)
  2. El Anbari, Mohammed; Mkhadri, Abdallah: Penalized regression combining the $ L_1$ norm and a correlation based penalty (2014)
  3. Paul, Debashis; Aue, Alexander: Random matrix theory in statistics: a review (2014)
  4. Wang, Y.; Daniels, M.J.: Computationally efficient banding of large covariance matrices for ordered data and connections to banding the inverse Cholesky factor (2014)
  5. Boonstra, Philip S.; Mukherjee, Bhramar; Taylor, Jeremy M.G.: Bayesian shrinkage methods for partially observed data with many predictors (2013)
  6. Cook, R.Dennis; Forzani, Liliana; Rothman, Adam J.: Prediction in abundant high-dimensional linear regression (2013)
  7. Hardin, Johanna; Garcia, Stephan Ramon; Golan, David: A method for generating realistic correlation matrices (2013)
  8. Cook, R.Dennis; Forzani, Liliana; Rothman, Adam J.: Estimating sufficient reductions of the predictors in abundant high-dimensional regressions (2012)
  9. Städler, Nicolas; Bühlmann, Peter: Missing values: sparse inverse covariance estimation and an extension to sparse regression (2012)
  10. Pourahmadi, Mohsen: Covariance estimation: the GLM and regularization perspectives (2011)
  11. Ahdesmäki, Miika; Strimmer, Korbinian: Feature selection in omics prediction problems using cat scores and false nondiscovery rate control (2010)
  12. Allen, Genevera I.; Tibshirani, Robert: Transposable regularized covariance models with an application to missing data imputation (2010)
  13. Witten, Daniela M.; Tibshirani, Robert: Covariance-regularized regression and classification for high dimensional problems (2009)