itdr: Integral Transformation Methods for SDR in Regression

The itdr() routine allows for the estimation of sufficient dimension reduction subspaces in univariate regression such as the central mean subspace or central subspace in regression. This is achieved using Fourier transformation methods proposed by Zhu and Zeng (2006) <doi:10.1198/016214506000000140>, convolution transformation methods proposed by Zeng and Zhu (2010) <doi:10.1016/j.jmva.2009.08.004>, and iterative Hessian transformation methods proposed by Cook and Li (2002) <doi:10.1214/aos/1021379861>. Additionally, mitdr() function provides optimal estimators for sufficient dimension reduction subspaces in multivariate regression by optimizing a discrepancy function using a Fourier transform approach proposed by Weng and Yin (2022) <doi:10.5705/ss.202020.0312>, and selects the sufficient variables using Fourier transform sparse inverse regression estimators proposed by Weng (2022) <doi:10.1016/j.csda.2021.107380>.

Version: 2.0.1
Depends: R (≥ 3.5.0)
Imports: stats, utils, MASS, geigen, magic, energy, tidyr
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-02-26
Author: Tharindu P. De Alwis ORCID iD [aut, cre], S. Yaser Samadi ORCID iD [ctb, aut], Jiaying Weng ORCID iD [ctb, aut]
Maintainer: Tharindu P. De Alwis <talwis at wpi.edu>
License: GPL-2 | GPL-3
NeedsCompilation: yes
Citation: itdr citation info
Materials: NEWS
CRAN checks: itdr results

Documentation:

Reference manual: itdr.pdf
Vignettes: itdr-vignette

Downloads:

Package source: itdr_2.0.1.tar.gz
Windows binaries: r-devel: itdr_2.0.1.zip, r-release: itdr_2.0.1.zip, r-oldrel: itdr_2.0.1.zip
macOS binaries: r-release (arm64): itdr_2.0.1.tgz, r-oldrel (arm64): itdr_2.0.1.tgz, r-release (x86_64): itdr_2.0.1.tgz
Old sources: itdr archive

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