Covariance-regularized regression and classification for high dimensional problems - Witten, Daniela M.; Tibshirani, Robert (Journal of the Royal Statistical Society. Series B, Statistical methodology, 2009)
Keywords: Classification; Coefficients; Covariance; Covariance matrices; Covariance regularization; data collection; Datasets; Discriminant analysis; Estimating techniques; Estimation; Estimation methods; Estimators; Exact sciences and technology; Gene expression; General topics; Generalized linear models; Least squares; Linear analysis; Linear inference, regression; Linear models; Linear regression; Mathematical procedures; Mathematics; Modeling; Multivariate analysis; n[double less-than sign]p; n≪p; prediction; Probability and statistics; Probability theory and stochastic processes; Regression; Regression analysis; Regression coefficients; Regulation; Sciences and techniques of general use; Statistical methods; Statistics; Stochastic processes; Studies; Variable selection; Ridge regression; Rank statistic; Generalized linear model; Covariance regularization; Prediction theory; Multivariate analysis; Stochastic process; Linear model; Penalty method; Parametric method; Covariance; Survival function; Inverse matrix; n « p; Log likelihood; Classification; Ill posed problem; Variable selection; Censored data; Discriminant analysis; Numerical linear algebra; Prediction; Regression; Statistical estimation; Covariance matrix; Survival; Regularization method; Statistical method; Statistical regression; Regression coefficient; Selection problem; Numerical analysis; Filtering theory; Regularization