Package: cocorresp
Type: Package
Title: Co-correspondence analysis ordination methods for community ecology
Version: 0.1-3
Date: 2005-11-30
Depends: vegan
Author: Original Matlab routines by C.J.F. ter Braak and A.P. Schaffers. R port by Gavin L. Simpson.
Function simpls based on simpls.fit (package pls) by Ron Wehrens and Bjorn-Helge Mevik.
Maintainer: Gavin L. Simpson <gavin.simpson@ucl.ac.uk>
Description: 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.
License: GPL Version 2
Encoding: UTF-8
Packaged: Wed Nov 30 12:56:28 2005; gavin

Package: cocorresp
Type: Package
Title: Co-correspondence analysis methods
Version: 0.1-6
Date: 2007-10-07
Depends: stats, graphics, vegan
Author: Original Matlab routines by C.J.F. ter Braak and A.P. Schaffers. R port by Gavin L. Simpson.
Function simpls based on simpls.fit (package pls) by Ron Wehrens and Bjorn-Helge Mevik.
Maintainer: Gavin L. Simpson <gavin.simpson@ucl.ac.uk>
Description: 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.
License: GPL-2
Packaged: Thu Dec 13 17:58:23 2007; gavin

Author: Original Matlab routines by C.J.F. ter Braak and A.P.
Schaffers. R port by Gavin L. Simpson. Function simpls based on
simpls.fit (package pls) by Ron Wehrens and Bjorn-Helge Mevik.
Description: 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