Principal Response Curves (PRC) for displaying multivariate main effects and interactions

Source: R/PRC-package.R

PRC creates 1d and 2d PRC-diagrams using Principal Response Curves analysis (van den Brink & ter Braak 1999). The main user functions are doPRC, plotPRC and plotPRC2d. The easiest example is the code demo PRC_pyrifos. The function doPRC is more general than and replaces vegan::prc.

References

ter Braak, C.J.F. (2023) Redundancy analysis includes analysis of variance-simultaneous component analysis (ASCA) and outperforms its extensions Chemometrics and Intelligent Laboratory Systems, 240 doi:10.1016/j.chemolab.2023.104898

van den Brink, P.J. & ter Braak, C.J.F. (1999) Principal Response Curves: Analysis of time-dependent multivariate responses of a biological community to stress. Environmental Toxicology and Chemistry, 18, 138-148. doi:10.1002/etc.5620180207

Oksanen, J., et al. (2022) vegan: Community Ecology Package. R package version 2.6-4. https://CRAN.R-project.org/package=vegan.

See also

doPRC, smoothPRC, prc