Package: nscancor
Authors@R: c( person("Christian", "Sigg", email =
        "christian@sigg-iten.ch", role = c("aut", "cph", "cre"),
        comment = c(ORCID = "0000-0003-1067-9224")), person("R Core
        team", role = c("cph", "ctb"), comment = "cancor() interface
        and documentation"))
Version: 0.7.0-6
Title: Non-Negative and Sparse CCA
Description: Two implementations of canonical correlation analysis
        (CCA) that are based on iterated regression. By choosing the
        appropriate regression algorithm for each data domain, it is
        possible to enforce sparsity, non-negativity or other kinds of
        constraints on the projection vectors. Multiple canonical
        variables are computed sequentially using a generalized
        deflation scheme, where the additional correlation not
        explained by previous variables is maximized. nscancor() is
        used to analyze paired data from two domains, and has the same
        interface as cancor() from the 'stats' package (plus some extra
        parameters). mcancor() is appropriate for analyzing data from
        three or more domains. See
        <https://sigg-iten.ch/learningbits/2014/01/20/canonical-correlation-analysis-under-constraints/>
        and Sigg et al. (2007) <doi:10.1109/MLSP.2007.4414315> for more
        details.
URL: https://sigg-iten.ch/research/
BugReports: https://github.com/chrsigg/nscancor/issues
License: GPL (>=2)
Depends: R (>= 3.6.0)
Imports: methods, stats
Suggests: CCA, glmnet, MASS, roxygen2, testthat (>= 0.8), V8
RoxygenNote: 7.2.3
Encoding: UTF-8
Repository: https://chrsigg.r-universe.dev
Date/Publication: 2023-04-05 19:12:25 UTC
RemoteUrl: https://github.com/chrsigg/nscancor
RemoteRef: HEAD
RemoteSha: 8f3eb56a577abee7643b0d82e53255456b256ab4
NeedsCompilation: no
Packaged: 2026-10-13 09:25:03 UTC; root
Author: Christian Sigg [aut, cph, cre] (ORCID:
    <https://orcid.org/0000-0003-1067-9224>),
  R Core team [cph, ctb] (cancor() interface and documentation)
Maintainer: Christian Sigg <christian@sigg-iten.ch>