sdim: An R Package for Supervised Dimension Reduction
Implements five factor extraction methods for asset pricing and macroeconomic forecasting: principal component analysis (PCA), partial least squares (PLS), scaled PCA (sPCA) of Huang, Jiang, Li, Tong, and Zhou (2022) <doi:10.1287/mnsc.2021.4020>, the reduced-rank approach (RRA) of He, Huang, Li, and Zhou (2023) <doi:10.1287/mnsc.2022.4563>, and Instrumented PCA (IPCA) of Kelly, Pruitt, and Su (2019) <doi:10.1016/j.jfineco.2019.05.001>.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | stats, graphics, Rcpp |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | frenchdata, knitr, readxl, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2026-07-11 |
| DOI: | 10.32614/CRAN.package.sdim |
| Author: | Gabriel Cabrera 
[aut, cre] |
| Maintainer: | Gabriel Cabrera <gabriel.cabrera.guz at gmail.com> |
| BugReports: | https://github.com/gabbocg/sdim/issues |
| License: | MIT + file LICENSE |
| URL: | https://gabbocg.github.io/sdim/, https://github.com/gabbocg/sdim |
| NeedsCompilation: | yes |
| Language: | en-GB |
| Materials: | README, NEWS |
| CRAN checks: | sdim results |
Documentation:
| Reference manual: | sdim.html , sdim.pdf |
| Vignettes: |
Replicating He et al. (2023) (source, R code) Replicating Huang et al. (2022) (source, R code) IPCA with the Grunfeld dataset (source, R code) Get started with sdim (source, R code) |
Downloads:
| Package source: | sdim_0.1.0.tar.gz |
| Windows binaries: | r-devel: sdim_0.1.0.zip, r-release: sdim_0.1.0.zip, r-oldrel: sdim_0.1.0.zip |
| macOS binaries: | r-release (arm64): sdim_0.1.0.tgz, r-oldrel (arm64): sdim_0.1.0.tgz, r-release (x86_64): sdim_0.1.0.tgz, r-oldrel (x86_64): sdim_0.1.0.tgz |
Linking:
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