Bootstrap error-adjusted single-sample technique
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Bootstrap Error-Adjusted Single-Sample Technique (BEST) is a nonparametric method for estimating the distribution of a sample.[1] It is based on a statistical method called bootstrapping. BEST provides advantages over other methods such as the Mahalanobis metric, because it does not assume equal covariance for all spectral groups and that each group is drawn for a normally distributed population.[2]