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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | sdrt_1.0.0.tar.gz |
65.1 KiB |
1.0.0 |
rolling linux/noble R-4.5 | sdrt_1.0.0.tar.gz |
65.2 KiB |
1.0.0 |
rolling source/ R- | sdrt_1.0.0.tar.gz |
23.9 KiB |
1.0.0 |
latest linux/jammy R-4.5 | sdrt_1.0.0.tar.gz |
65.1 KiB |
1.0.0 |
latest linux/noble R-4.5 | sdrt_1.0.0.tar.gz |
65.2 KiB |
1.0.0 |
latest source/ R- | sdrt_1.0.0.tar.gz |
23.9 KiB |
1.0.0 |
2026-04-26 source/ R- | sdrt_1.0.0.tar.gz |
23.9 KiB |
1.0.0 |
2026-04-23 source/ R- | sdrt_1.0.0.tar.gz |
23.9 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | sdrt_1.0.0.zip |
74.3 KiB |
1.0.0 |
2025-04-20 source/ R- | sdrt_1.0.0.tar.gz |
23.9 KiB |