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sdrt  

Estimating the Sufficient Dimension Reduction Subspaces in Time Series
View on CRAN: Click here


Download and install sdrt package within the R console
Install from CRAN:
install.packages("sdrt")

Install from Github:
library("remotes")
install_github("cran/sdrt")

Install by package version:
library("remotes")
install_version("sdrt", "1.0.0")



Attach the package and use:
library("sdrt")
Maintained by
Tharindu P. De Alwis
[Scholar Profile | Author Map]
First Published: 2024-03-28
Latest Update: 2024-03-28
Description:
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) and the Nadaraya-Watson kernel smoother method proposed by Park et al. (2009) 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.
How to cite:
Tharindu P. De Alwis (2024). sdrt: Estimating the Sufficient Dimension Reduction Subspaces in Time Series. R package version 1.0.0, https://cran.r-project.org/web/packages/sdrt. Accessed 03 May. 2025.
Previous versions and publish date:
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Complete documentation for sdrt
Functions, R codes and Examples using the sdrt R package
Full sdrt package functions and examples
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