Package: sdrt 1.0.0
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.
Authors:
sdrt_1.0.0.tar.gz
sdrt_1.0.0.zip(r-4.5)sdrt_1.0.0.zip(r-4.4)sdrt_1.0.0.zip(r-4.3)
sdrt_1.0.0.tgz(r-4.4-x86_64)sdrt_1.0.0.tgz(r-4.4-arm64)sdrt_1.0.0.tgz(r-4.3-x86_64)sdrt_1.0.0.tgz(r-4.3-arm64)
sdrt_1.0.0.tar.gz(r-4.5-noble)sdrt_1.0.0.tar.gz(r-4.4-noble)
sdrt_1.0.0.tgz(r-4.4-emscripten)sdrt_1.0.0.tgz(r-4.3-emscripten)
sdrt.pdf |sdrt.html✨
sdrt/json (API)
NEWS
| # Install 'sdrt' in R: |
| install.packages('sdrt', repos = c('https://tharindupdealwis.r-universe.dev', 'https://cloud.r-project.org')) |
- lynx - Canadian Lynx Data.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 months agofrom:be255fb64b. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 25 2024 |
| R-4.5-win-x86_64 | OK | Oct 25 2024 |
| R-4.5-linux-x86_64 | OK | Oct 25 2024 |
| R-4.4-win-x86_64 | OK | Oct 25 2024 |
| R-4.4-mac-x86_64 | OK | Oct 25 2024 |
| R-4.4-mac-aarch64 | OK | Oct 25 2024 |
| R-4.3-win-x86_64 | OK | Oct 25 2024 |
| R-4.3-mac-x86_64 | OK | Oct 25 2024 |
| R-4.3-mac-aarch64 | OK | Oct 25 2024 |
Exports:distpd.bootssdrtsigma_u
Dependencies:curlGPArotationjsonlitelatticemnormtnlmepracmapsychquadprogquantmodtseriesTTRxtszoo
