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Shrinkage of the covariance matrix using the Oracle approximation

Source: R/fun_export.R
shrink_oasd.Rd

Shrinkage of the covariance matrix according to the Oracle Approximating Shrinkage (OAS) of Chen et al. (2009) and Ando and Xiao (2023).

Usage

shrink_oasd(x, mse = TRUE)

Arguments

x

A numeric matrix containing the in-sample residuals.

mse

If TRUE (default), the residuals used to compute the covariance matrix are not mean-corrected.

Value

A shrunk covariance matrix.

References

Ando, S., and Xiao, M. (2023), High-dimensional covariance matrix estimation: shrinkage toward a diagonal target. IMF Working Papers, 2023(257), A001. doi:10.5089/9798400260780.001.A001

Chen, Y., Wiesel, A., and Hero, A. O. (2009), Shrinkage estimation of high dimensional covariance matrices, 2009 IEEE international conference on acoustics, speech and signal processing, 2937–2940. IEEE.

See also

Utilities: FoReco2matrix(), aggts(), balance_hierarchy(), commat(), csprojmat(), cstools(), ctprojmat(), cttools(), df2aggmat(), lcmat(), recoinfo(), res2matrix(), set_bounds(), shrink_estim(), teprojmat(), tetools(), unbalance_hierarchy()