Canonical Correlation Analysis via Reduced Rank Regression
Overview
Canonical correlation analysis (CCA) via reduced-rank regression with support for regularization and cross-validation. Several methods for estimating CCA in high-dimensional settings are implemented. The first set of methods, cca_rrr() (and variants: cca_group_rrr() and cca_graph_rrr()), assumes that one dataset is high-dimensional and the other is low-dimensional, while the second, ecca() (for Efficient CCA) assumes that both datasets are high-dimensional. For both methods, standard l1 regularization as well as group-lasso regularization are available. cca_graph_rrr further supports total variation regularization when there is a known graph structure among the variables of the high-dimensional dataset. In this case, the loadings of the canonical directions of the high-dimensional dataset are assumed to be smooth on the graph. For more details see Donnat and Tuzhilina (2024) doi:10.48550/arXiv.2405.19539 and Wu, Tuzhilina and Donnat (2025) doi:10.48550/arXiv.2507.11160.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK7 OK2026-06-14
- ERROR5 OK, 9 ERROR2026-03-10
Documentation
- Help pages
- 21 (1 internal)includes a package overview page
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 15%
- Documented parameters
- 94%
- Return-value docs
- 100%
- Help pages citing references
- 0%
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Code & Tests
People & History
Pick two releases to compare their code metrics.
- unarchivedReturned to CRAN2026-06-13
- 0.1.2Latest
- archivedRemoved from CRAN2026-05-15issues were not corrected in time
- unarchivedReturned to CRAN2026-04-29
- 0.1.12026-04-29 · diff ↗
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2026-04-11issues were not corrected despite reminders
- 0.1.02025-09-16
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-09-16
- Total releases
- 3 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 58 KB
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