Various plotting procedures for pcanova objects.
# S3 method for pcanova
scoreplot(object, factor = 1, comps = 1:2, col = "factor", ...)The plotting routines have no return.
pcanova object.
integer/character for selecting a model factor.
integer vector of selected components.
character for selecting a factor to use for colouring
(default = first factor) or ordinary colour specifications.
additional arguments to underlying methods.
Usage of the functions are shown using generics in the examples in pcanova.
Plot routines are available as
scoreplot.pcanova and loadingplot.pcanova.
Luciano G, Næs T. Interpreting sensory data by combining principal component analysis and analysis of variance. Food Qual Prefer. 2009;20(3):167-175.
Main methods: asca, apca, limmpca, msca, pcanova, prc and permanova.
Workhorse function underpinning most methods: hdanova.
Extraction of results and plotting: asca_results, asca_plots, pcanova_results and pcanova_plots