Metric Oja depth, new statistical tool for estimating the most central objects
提出度量Oja深度，适用于图像、文本等任意对象数据，用来找出样本中最中心的对象，并与三种深度函数做了比较。
The Oja depth (simplicial volume depth) is one of the classical statistical techniques for measuring the central tendency of data in multivariate space. Despite the widespread emergence of object data like images, texts, matrices or graphs, a well-developed and suitable version of Oja depth for object data is lacking. To address this shortcoming, a novel measure of statistical depth, the metric Oja depth applicable to any object data, is proposed. Two competing strategies are used for optimizing metric depth functions, i.e., for finding the deepest objects among the sample. The performance of the metric Oja depth is compared with three other depth functions (half-space, lens, and spatial) in diverse data scenarios.