MKendall: Matrix Kendall's Tau and Matrix Elliptical Factor Model
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) <doi:10.48550/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.
| Version: |
1.5-4 |
| Published: |
2024-03-11 |
| DOI: |
10.32614/CRAN.package.MKendall |
| Author: |
Yong He [aut],
Yalin Wang [aut, cre],
Long Yu [aut],
Wang Zhou [aut],
Wenxin Zhou [aut] |
| Maintainer: |
Yalin Wang <wangyalin at mail.sdu.edu.cn> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| CRAN checks: |
MKendall results |
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