GIS.m: Nonlinear shrinkage derived under the Symmetrized Kullback-Leibler loss, called geometric-inverse shrinkage (GIS). covMarket: Linear shrinkage towards a one-factor market model, where the factor is defined as the cross-sectional average of all the random variables thanks to the idiosyncratic volatility of the residuals, the target preserves the diagonal of the sample covariance matrix.covDiag: Linear shrinkage towards diagonal matrix the target preserves the diagonal of the sample covariance matrix and all the covariances are zero.covCor: Linear shrinkage towards constant-correlation matrix the target preserves the diagonal of the sample covariance matrix and all correlation coefficients are the same.cov2Para: Linear shrinkage towards two-parameter matrix all the variances are the same, all the covariances are the same.cov1Para: Linear shrinkage towards one-parameter matrix all the variances are the same, all the covariances are zero. PURPOSE: To provide fast and accurate estimators of the covariance matrix based on linear and nonlinear shrinkage for general applications. A Package for Shrinkage Estimation of Covariance Matrices
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