Optimal estimation of a large-dimensional covariance matrix under Stein’s loss
نویسندگان
چکیده
منابع مشابه
Optimal estimation of a large-dimensional covariance matrix under Stein's loss
This paper revisits the methodology of Stein (1975, 1986) for estimating a covariance matrix in the setting where the number of variables can be of the same magnitude as the sample size. Stein proposed to keep the eigenvectors of the sample covariance matrix but to shrink the eigenvalues. By minimizing an unbiased estimator of risk, Stein derived an ‘optimal’ shrinkage transformation. Unfortuna...
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ژورنال
عنوان ژورنال: Bernoulli
سال: 2018
ISSN: 1350-7265
DOI: 10.3150/17-bej979