CCA: Canonical Correspondence Analysis

In MultBiplotR: Multivariate Analysis Using Biplots in R

Canonical Correspondence Analysis

Description

Calculates the solution of a Canonical Correspondence Analysis Biplot

Usage

CCA(P, Z, alpha = 1, dimens = 4)

Arguments

P	Abundance Matrix of sites by species.
Z	Environmental variables measured at the same sites
alpha	Alpha for the biplot decomposition [0,1]. With alpha=1 the emphasis is on the sites and with alpha=0 the emphasis is on the species
dimens	Dimension of the solution

Details

A pair of ecological tables, made of a species abundance matrix and an environmental variables matrix measured at the same sampling sites, is usually analyzed by Canonical Correspondence Analysis (CCA) (Ter BRAAK, 1986). CCA can be considered as a Correspondence Analysis (CA) in which the ordination axis are constrained to be linear combinations of the environmental variables. Recently the procedure has been extended to other disciplines as Sociology or Psichology and it is potentially useful in many other fields.

Value

A CCA solution object

Author(s)

Jose Luis vicente Villardon

References

Ter Braak, C. J. (1986). Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology, 67(5), 1167-1179.

Johnson, K. W., & Altman, N. S. (1999). Canonical correspondence analysis as an approximation to Gaussian ordination. Environmetrics, 10(1), 39-52.

Graffelman, J. (2001). Quality statistics in canonical correspondence analysis. Environmetrics, 12(5), 485-497.

Graffelman, J., & Tuft, R. (2004). Site scores and conditional biplots in canonical correspondence analysis. Environmetrics, 15(1), 67-80.

Greenacre, M. (2010). Canonical correspondence analysis in social science research (pp. 279-286). Springer Berlin Heidelberg.

Examples

data(riano)
Sp=riano[,3:15]
Env=riano[,16:25]
ccabip=CCA(Sp, Env)
plot(ccabip)

MultBiplotR documentation built on Nov. 21, 2023, 5:08 p.m.