Co-correspondence analysis with R
cocorresp fits symmetric and predictive co-correspondence (CoCA) models in R.
Fits predictive and symmetric co-correspondence analysis (CoCA) models to relate one data matrix to another data matrix. More specifically, CoCA maximises the weighted covariance between the weighted averaged species scores of one community and the weighted averaged species scores of another community. CoCA attempts to find patterns that are common to both communitities.
The main interface function is
coca which accepts a
formula or two community data matrices. An appropriate formula is
Y ~ ., data = X and the associated
data object from which
. will be looked up. The
method argument is used to select from the two forms of CoCA:
method = "predictive"for predictive CoCA (the default), and
method = "symmetric"for symmetric CoCA.
The cocorresp package is based on original Matlab routines by C.J.F. ter Braak and A.P. Schaffers. The R port was by Gavin L. Simpson. Function
cocorresp::simpls() is largely based on
simpls.fit() from the pls package of Ron Wehrens and Bjorn-Helge Mevik.
cocorresp is available from CRAN; install the latest release using
To install the development version, use the devtools package (you may need to install devtools first)