plot_variance_explained {nzilbb.vowels} | R Documentation |
pca_test
objectThe variance explained by each PC in a dataset is plotted with confidence
intervals generated by bootstrapping and a null distribution generated by
permutation. The function accepts the result of calling the pca_test
function.
plot_variance_explained(pca_test, pc_max = NA, percent = TRUE)
pca_test |
an object of class pca_test_results generated by |
pc_max |
the maximum number of PCs to plot. If NA, plot all PCs. |
percent |
if TRUE, represent variance explained as a percentage. If FALSE, represent as eigenvalues. |
By default, variance explained is represented as a percentage. If the
argument percent
is set to FALSE, then the variance explained is
represented by the eigenvalues corresponding to each PC.
ggplot
object.
onze_pca <- pca_test(onze_intercepts |> dplyr::select(-speaker), n = 10)
# Plot with percentages
plot_variance_explained(onze_pca)
# Plot with eigenvalues and only the first 5 PCs.
plot_variance_explained(onze_pca, pc_max = 5, percent = FALSE)