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HDTSA: High Dimensional Time Series Analysis Tools

Procedures for high-dimensional time series analysis including factor analysis proposed by Lam and Yao (2012) <doi:10.1214/12-AOS970> and Chang, Guo and Yao (2015) <doi:10.1016/j.jeconom.2015.03.024>,martingale difference test proposed by Chang, Jiang and Shao (2022) <doi:10.1016/j.jeconom.2022.09.001> in press,principal component analysis proposed by Chang, Guo and Yao (2018) <doi:10.1214/17-AOS1613>, identifying cointegration proposed by Zhang, Robinson and Yao (2019) <doi:10.1080/01621459.2018.1458620>, unit root test proposed by Chang, Cheng and Yao (2021) <doi:10.1093/biomet/asab034>, white noise test proposed by Chang, Yao and Zhou (2017) <doi:10.1093/biomet/asw066>, CP-decomposition for high-dimensional matrix time series proposed by Chang, He, Yang and Yao(2023) <doi:10.1093/jrsssb/qkac011> and Chang, Du, Huang and Yao (2024+), and Statistical inference for high-dimensional spectral density matrix porposed by Chang, Jiang, McElroy and Shao (2023) <doi:10.48550/arXiv.2212.13686>.

Version: 1.0.4
Depends: R (≥ 3.5.0)
Imports: stats, Rcpp, clime, sandwich, methods, MASS, geigen, jointDiag
LinkingTo: Rcpp, RcppEigen
Suggests: knitr
Published: 2024-09-03
DOI: 10.32614/CRAN.package.HDTSA
Author: Chen Lin [aut, cre], Jinyuan Chang [aut], Qiwei Yao [aut]
Maintainer: Chen Lin <linchen at smail.swufe.edu.cn>
BugReports: https://github.com/Linc2021/HDTSA/issues
License: GPL-3
URL: https://github.com/Linc2021/HDTSA
NeedsCompilation: yes
In views: TimeSeries
CRAN checks: HDTSA results

Documentation:

Reference manual: HDTSA.pdf

Downloads:

Package source: HDTSA_1.0.4.tar.gz
Windows binaries: r-devel: HDTSA_1.0.4.zip, r-release: HDTSA_1.0.4.zip, r-oldrel: HDTSA_1.0.4.zip
macOS binaries: r-release (arm64): HDTSA_1.0.4.tgz, r-oldrel (arm64): HDTSA_1.0.4.tgz, r-release (x86_64): HDTSA_1.0.4.tgz, r-oldrel (x86_64): HDTSA_1.0.4.tgz
Old sources: HDTSA archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=HDTSA to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.