This function creates a visualization of the results of the PCA applied on a sample of QTS without returning the plot data as an object.
Arguments
- x
An object of class
prcomp_qts
as produced by theprcomp.qts_sample()
method.- what
A string specifying what kind of visualization the user wants to perform. Choices are words starting with
PC
and ending with a PC number (in which case the mean QTS is displayed along with its perturbations due to the required PC) orscores
(in which case individuals are projected on the required plane). Defaults toPC1
.- ...
If
what = "PC?"
, the user can specify whether to plot the QTS in the tangent space or in the original space by providing a boolean argumentoriginal_space
which defaults toTRUE
. Ifwhat = "scores"
, the user can specify the plane onto which the individuals will be projected by providing a length-2 integer vector argumentplane
which defaults to1:2
.
Examples
df <- as_qts_sample(vespa64$igp[1:16])
res_pca <- prcomp(df)
#> ℹ The maximum number of principal component is 15.
# You can plot the effect of a PC on the mean
plot(res_pca, what = "PC1")
#> The `original_space` boolean argument is not specified. Defaulting to TRUE.
# You can plot the data points in a PC plane
plot(res_pca, what = "scores")
#> The `plane` length-2 integer vector argument is not specified. Defaulting to
#> 1:2.