Abstract
ABSTRACTAs a multivariate generalization of the univariate median, projection depth median (PM) is unique, and enjoys a very high breakdown point, much higher than its affine equivariant competitors such as halfspace depth median. Nevertheless, its computation is challenging. Until now PM can only be exactly computed efficiently for bivariate data. In this article, we develop an algorithm to approximate PM in higher dimensions. Some data examples indicate that the proposed algorithm performs well in terms of both accuracy and efficiency. As an application, we investigate the finite sample relative efficiency of PM by utilizing the Matlab implementation of this algorithm.
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