| pcanova_plots | R Documentation |
Various plotting procedures for pcanova objects.
## S3 method for class 'pcanova'
scoreplot(object, factor = 1, comps = 1:2, col = "factor", ...)
object |
|
factor |
|
comps |
|
col |
|
... |
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.
The plotting routines have no return.
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
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