Package: RFCCA
Title: Random Forest with Canonical Correlation Analysis
Version: 2.0.0
Authors@R: 
    c(person(given = "Cansu", family = "Alakus", role = c("aut", "cre"), email = "cansu.alakus@hec.ca"),
      person(given = "Denis", family = "Larocque", role = c("aut"), email = "denis.larocque@hec.ca"),
      person(given = "Aurelie", family = "Labbe", role = c("aut"), email = "aurelie.labbe@hec.ca"),
      person(given = "Hemant", family = "Ishwaran", role = c("ctb"), comment = "Author of included randomForestSRC codes"),
      person(given = "Udaya B.", family = "Kogalur", role = c("ctb"), comment = "Author of included randomForestSRC codes"),
      person("Intel Corporation", role = c("cph"), comment = "Copyright holder of included LAPACKE codes"),
      person(given = "Keita", family = "Teranishi", role = c("ctb"), comment = "Author of included cblas_dgemm.c codes"))
Description: Random Forest with Canonical Correlation Analysis (RFCCA) is a 
  random forest method for estimating the canonical correlations between two 
  sets of variables depending on the subject-related covariates. The trees are 
  built with a splitting rule specifically designed to partition the data to 
  maximize the canonical correlation heterogeneity between child nodes. The 
  method is described in Alakus et al. (2021) <doi:10.1093/bioinformatics/btab158>. 
  'RFCCA' uses 'randomForestSRC' package (Ishwaran and Kogalur, 2020) by 
  freezing at the version 2.9.3. The custom splitting rule feature is utilised 
  to apply the proposed splitting rule. The 'randomForestSRC' package implements 
  'OpenMP' by default, contingent upon the support provided by the target 
  architecture and operating system. In this package, 'LAPACK' and 'BLAS' 
  libraries are used for matrix decompositions.
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.0
Imports: CCA, PMA
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
URL: https://github.com/calakus/RFCCA
BugReports: https://github.com/calakus/RFCCA/issues
NeedsCompilation: yes
Packaged: 2024-02-06 18:11:26 UTC; cansualakus
Author: Cansu Alakus [aut, cre],
  Denis Larocque [aut],
  Aurelie Labbe [aut],
  Hemant Ishwaran [ctb] (Author of included randomForestSRC codes),
  Udaya B. Kogalur [ctb] (Author of included randomForestSRC codes),
  Intel Corporation [cph] (Copyright holder of included LAPACKE codes),
  Keita Teranishi [ctb] (Author of included cblas_dgemm.c codes)
Maintainer: Cansu Alakus <cansu.alakus@hec.ca>
Repository: CRAN
Date/Publication: 2024-02-09 00:10:02 UTC
