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novelist (version 1.0)

delta.star: Compute optimal shrinkage intensities for given thresholding levels

Description

Compute optimal shrinkage intensities for given thresholding levels by minimizing the mean square error.

Usage

delta.star(data, thres.range)

Arguments

data
dataset. A $n$ by $p$ matrix.
thres.range
range of thresholding levels. The default value is thres.range=seq(0,1,by=0.05).

Value

delta.star
the pairs of ($\lambda,\delta*(\lambda))$.
cov
the array of NOVELIST estimators of covariance matrices with the pairs of ($\lambda,\delta*(\lambda))$.
cor
the array of NOVELIST estimators of correlation matrices with the pairs of ($\lambda,\delta*(\lambda))$.

Details

Compute the optimal shrinkage internsity $\delta*(\lambda)$ for any given thresholding level $\lambda$ by minimizing the mean squared error of the NOVELIST covariance estimators to its true covariance matrices.The details of the method are explained by Huang and Fryzlewicz (2015) and Ledoit and Wolf (2003).

References

Huang, N. & Fryzlewicz, P. (2015), "NOVELIST estimator of large correlation and covariance matrices and their inverses". Preprint.

Ledoit, O. & Wolf, M. (2003), "Improved estimation of the covariance matrix of stock returns with an application to portfolio selection." Journal of Empirical Finance 10, 603-621.