Package: RFCCA
Title: Random Forest with Canonical Correlation Analysis
Version: 1.0.11
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. LAPACK and BLAS libraries are used for matrix 
  decompositions. The ‘RFCCA’ package includes the header files ‘lapacke.h’ and 
  ‘cblas.h’ from the LAPACK and BLAS libraries. The LAPACK library is licensed 
  under modified BSD license. 
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: 2023-09-18 19:31:59 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: 2023-09-19 08:20:02 UTC
