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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.
Getting started
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Package details |
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| Author | Tharindu P. De Alwis [aut, cre] (<https://orcid.org/0000-0002-3446-0502>), S. Yaser Samadi [ctb, aut] (<https://orcid.org/0000-0002-6121-0234>) |
| Maintainer | Tharindu P. De Alwis <talwis@wpi.edu> |
| License | GPL-2 | GPL-3 |
| Version | 1.0.0 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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