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  "Author": "Yong He [aut], Yalin Wang [aut, cre], Long Yu [aut], Wang Zhou\n[aut], Wenxin Zhou [aut]",
  "Maintainer": "Yalin Wang <wangyalin@mail.sdu.edu.cn>",
  "Description": "Large-scale matrix-variate data have been widely observed\nnowadays in various research areas such as finance, signal\nprocessing and medical imaging. Modelling matrix-valued data by\nmatrix-elliptical family not only provides a flexible way to\nhandle heavy-tail property and tail dependencies, but also\nmaintains the intrinsic row and column structure of random\nmatrices. We proposed a new tool named matrix Kendall's tau\nwhich is efficient for analyzing random elliptical matrices. By\napplying this new type of Kendell’s tau to the matrix\nelliptical factor model, we propose a Matrix-type Robust\nTwo-Step (MRTS) method to estimate the loading and factor\nspaces. See the details in He at al. (2022) <arXiv:2207.09633>.\nIn this package, we provide the algorithms for calculating\nsample matrix Kendall's tau, the MRTS method and the Matrix\nKendall's tau Eigenvalue-Ratio (MKER) method which is used for\ndetermining the number of factors.",
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