MKendall

Description

Large-scale matrix-variate data have been widely observed nowadays in various research areas such as finance, signal processing and medical imaging. Modelling matrix-valued data by matrix-elliptical family not only provides a flexible way to handle heavy-tail property and tail dependencies, but also maintains the intrinsic row and column structure of random matrices. We proposed a new tool named matrix Kendall's tau which is efficient for analyzing random elliptical matrices. By applying this new type of Kendell’s tau to the matrix elliptical factor model, we propose a Matrix-type Robust Two-Step (MRTS) method to estimate the loading and factor spaces. See the details in He at al. (2022) <arXiv:2207.09633>. In this package, we provide the algorithms for calculating sample matrix Kendall's tau, the MRTS method and the Matrix Kendall's tau Eigenvalue-Ratio (MKER) method which is used for determining the number of factors.

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Maintainer: ‘Yalin Wang <wangyalin@mail.sdu.edu.cn>’

The Description field contains
  (2022) <arXiv:2207.09633>. In this package, we provide the algorithms
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

Maintainer: ‘Yalin Wang <wangyalin@mail.sdu.edu.cn>’

The Description field contains
  (2022) <arXiv:2207.09633>. In this package, we provide the algorithms
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

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Maintainer: ‘Yalin Wang <wangyalin@mail.sdu.edu.cn>’

The Description field contains
  (2022) <arXiv:2207.09633>. In this package, we provide the algorithms
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

Maintainer: ‘Yalin Wang <wangyalin@mail.sdu.edu.cn>’

The Description field contains
  (2022) <arXiv:2207.09633>. In this package, we provide the algorithms
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

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