(Robust) Canonical Correlation Analysis via Projection Pursuit

Canonical correlation analysis and maximum correlation via projection pursuit, as well as fast implementations of correlation estimators, with a focus on robust and non-parametric methods.


News

Changes in ccaPP version 0.3.2

+ Added references for maxCorGrid() and permTest().

+ Added vignette 'ccaPP-intro'.

Changes in ccaPP version 0.3.1

+ Added 'diabetes' data from Andrews & Herzberg (1985).

+ Print method and help file of permutation tests no longer use the term 
  'independence'.

+ Functions for robust CCA now standardize dummy variables with mean and 
  standard deviation.

+ Bugfix in functions for CCA: R session no longer crashes for higher-order 
  canonical correlations in case of high-dimensional data.

Changes in ccaPP version 0.3.0

+ Standardization in functions for CCA and maximum correlation is now 
  optional.

+ Functions for CCA and maximum correlation now return center and scale 
  estimates from standardization.

+ Slightly faster version of fastMedian().

+ Function permTest() now allows to supply permutations as an argument.

+ Bugfix in functions for CCA concerning side constraints for higher-order 
  canonical correlations.

+ Bugfix in functions for CCA: reduced data for higher-order canonical 
  correlations no longer standardized.

+ Bugfix in corM(): robust starting values now work with dummy variables.

+ Renamed internal C++ function rank() to fix error with clang++ under 
  OS X Mavericks.

Changes in ccaPP version 0.2.0

+ Functions ccaGrid() and ccaProj() now force consistency of the Spearman, 
  Kendall and quadrant correlation.

+ New functions maxCorGrid() and maxCorProj() for maximum correlation, 
  which retain the argument for consistency of the Spearman, Kendall and 
  quadrant correlation.

+ permTest(): now using the new functions maxCorGrid() and maxCorProj() 
  rather than ccaGrid() and ccaProj().

+ permTest(): argument 'cl' is now preferred over argument 'ncores' for 
  parallel computing.

+ Added fallback mode for robust standardization if the MAD of a variable 
  is zero.

+ Bugfix in ccaGrid() and its wrapper CCAgrid: seed for the random number 
  generator is no longer ignored.

+ Bugfix in CCAproj(): now correctly wrapped around ccaProj().

Changes in ccaPP version 0.1.1

+ Using package parallel now to detect the number of available processor 
  cores rather than OpenMP.

+ Internally created parallel cluster in permTest() is now stopped via 
  on.exit().

+ Bugfix in permTest(): random number streams for parallel clusters 
  supplied by the user are only reset if a seed is supplied.

Reference manual

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install.packages("ccaPP")

0.3.2 by Andreas Alfons, 3 years ago


Browse source code at https://github.com/cran/ccaPP


Authors: Andreas Alfons [aut, cre] , David Simcha [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp

Depends on parallel, pcaPP, robustbase

Suggests knitr, mvtnorm

Linking to Rcpp, RcppArmadillo


Suggested by yaImpute.


See at CRAN