tensorTS: Factor and Autoregressive Models for Tensor Time Series

Factor and autoregressive models for matrix and tensor valued time series. We provide functions for estimation, simulation and prediction. The models are discussed in Chen et al (2020) <doi:10.1016/j.jeconom.2020.07.015>, Chen et al (2020) <arXiv:1905.07530>, and Han et al (2020) <arXiv:2006.02611>.

Version: 0.1.1
Depends: tensor, rTensor, expm
Imports: methods, stats, MASS, abind, Matrix, pracma, graphics
Published: 2021-04-22
Author: Zebang Li [aut, cre], Ruofan Yu [aut], Rong Chen [aut], Yuefeng Han [aut], Han Xiao [aut], Dan Yang [aut]
Maintainer: Zebang Li <zl326 at stat.rutgers.edu>
BugReports: https://github.com/ZeBang/tensorTS/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/zebang/tensorTS
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: tensorTS results

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Reference manual: tensorTS.pdf
Package source: tensorTS_0.1.1.tar.gz
Windows binaries: r-devel: tensorTS_0.1.1.zip, r-release: tensorTS_0.1.1.zip, r-oldrel: tensorTS_0.1.1.zip
macOS binaries: r-release (arm64): tensorTS_0.1.1.tgz, r-release (x86_64): tensorTS_0.1.1.tgz, r-oldrel: tensorTS_0.1.1.tgz
Old sources: tensorTS archive

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