ccar3

Description

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>.

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Missing or unexported object: ‘CVXR::solve’

Missing or unexported object: ‘CVXR::solve’

Missing or unexported object: ‘CVXR::solve’

Missing or unexported object: ‘CVXR::solve’

Running ‘testthat.R’ [53s/43s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional 
...[truncated]...
  7.             ├─parallel::recvOneData(cl)
   8.             └─parallel:::recvOneData.SOCKcluster(cl)
   9.               └─base::unserialize(socklist[[n]])
  
  [ FAIL 5 | WARN 0 | SKIP 0 | PASS 101 ]
  Error:
  ! Test failures.
  Execution halted

Missing or unexported object: 'CVXR::solve'

Missing or unexported object: ‘CVXR::solve’

Missing or unexported object: 'CVXR::solve'

Missing or unexported object: 'CVXR::solve'

Dependency Network

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Sep 16, 2025. Releases before tracking aren’t shown.