CIRJE-F-970 | "Comparison of Linear Shrinkage Estimators of a Large Covariance Matrix in Normal and Non-normal Distributions" |
Author Name | Ikeda, Yuki, Tatsuya Kubokawa and Muni S. Srivastava |
Date | March 2015 |
Full Paper | PDF file |
Remarks | Subsequently published in Computational Statistics and Data Analysis, 95, 95-108, 2016. |
Abstract | The problem of estimating the large covariance matrix of both normal and non-normal distributions is addressed. In convex combinations of the sample covariance matrix and the identity matrix multiplied by a scalor statistic, we suggest a new estimator of the optimal weight based on exact or approximately unbiased estimators of the numerator and denominator of the optimal weight in non-normal cases. It is also demonstrated that the estimators given in the literature have second-order biases. It is numerically shown that the proposed estimator has a good risk performance. |