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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
|
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 |
Reference manual: | sdrt.pdf |
Vignettes: |
sdrt-vignette |
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 |
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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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