Covariance is a measure of how much two variables change together.
To estimate the covariance matrix, Ledoit and Wolf (2004) suggests using the matrix obtained from the sample covariance matrix through a transformation called shrinkage.
The estimator and some intermediate values computed by the algorithm.
This class computes the Covariance matrix of a matrix, where the (i, j) entry is the covariance of the i-th column and j-th column of the matrix.
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