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In this article, we propose a family of flexible shrinkage estimators which can use geometric or arithmetic means of sample variances of all genes as the target statistic for shrinkage and also allow the non-normal distribution of the data. The optimal shrinkage parameters are derived under the squared log error loss function and estimated by consistent estimators under a general asymptotic framework. The proposed estimators were evaluated through a series of Monte-Carlo simulation studies and applied to real data from a gene expression study of leukemia patients.

A family of flexible shrinkage estimators for the variances of high-dimensional gene expressions