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sdrt: Estimating the Sufficient Dimension Reduction Subspaces in Time Series

The sdrt() function is designed for estimating subspaces for Sufficient Dimension Reduction (SDR) in time series, with a specific focus on the Time Series Central Mean subspace (TS-CMS). The package employs the Fourier transformation method proposed by Samadi and De Alwis (2023) <doi:10.48550/arXiv.2312.02110> and the Nadaraya-Watson kernel smoother method proposed by Park et al. (2009) <doi:10.1198/jcgs.2009.08076> for estimating the TS-CMS. The package provides tools for estimating distances between subspaces and includes functions for selecting model parameters using the Fourier transformation method.

Version: 1.0.0
Depends: R (≥ 3.5.0), stats
Imports: psych, tseries, pracma
Suggests: rmarkdown, knitr
Published: 2024-03-28
DOI: 10.32614/CRAN.package.sdrt
Author: Tharindu P. De Alwis ORCID iD [aut, cre], S. Yaser Samadi ORCID iD [ctb, aut]
Maintainer: Tharindu P. De Alwis <talwis at wpi.edu>
License: GPL-2 | GPL-3
NeedsCompilation: yes
Citation: sdrt citation info
Materials: NEWS
In views: TimeSeries
CRAN checks: sdrt results

Documentation:

Reference manual: sdrt.pdf
Vignettes: sdrt-vignette

Downloads:

Package source: sdrt_1.0.0.tar.gz
Windows binaries: r-devel: sdrt_1.0.0.zip, r-release: sdrt_1.0.0.zip, r-oldrel: sdrt_1.0.0.zip
macOS binaries: r-release (arm64): sdrt_1.0.0.tgz, r-oldrel (arm64): sdrt_1.0.0.tgz, r-release (x86_64): sdrt_1.0.0.tgz, r-oldrel (x86_64): sdrt_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=sdrt 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.
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