Package: MKendall
Type: Package
Title: Matrix Kendall's Tau and Matrix Elliptical Factor Model
Version: 1.5-4
Authors@R: c(person("Yong","He",role=c("aut")),person("Yalin","Wang",role=c("aut","cre"),email="wangyalin@mail.sdu.edu.cn"),person("Long","Yu",role=c("aut")),person("Wang","Zhou",role=c("aut")),person("Wenxin","Zhou",role=c("aut")))
Author: Yong He [aut], Yalin Wang [aut, cre], Long Yu [aut], Wang Zhou
        [aut], Wenxin Zhou [aut]
Maintainer: Yalin Wang <wangyalin@mail.sdu.edu.cn>
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.
License: GPL-2
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-09 07:53:09 UTC; root
Repository: https://wangyalin09.r-universe.dev
Date/Publication: 2024-03-12 02:29:54 UTC
RemoteUrl: https://github.com/cran/MKendall
RemoteRef: HEAD
RemoteSha: ef74a81d3b243751be248f37e972f7bc453de01e