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
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

Documentation:

Reference manual:

MKendall.pdf

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Package source:	MKendall_1.5-4.tar.gz
Windows binaries:	r-devel: MKendall_1.5-4.zip, r-release: MKendall_1.5-4.zip, r-oldrel: MKendall_1.5-4.zip
macOS binaries:	r-release (arm64): MKendall_1.5-4.tgz, r-oldrel (arm64): MKendall_1.5-4.tgz, r-release (x86_64): MKendall_1.5-4.tgz, r-oldrel (x86_64): MKendall_1.5-4.tgz

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