Plot PC loadings in vowel space

Plot loadings from a PCA analysis carried out on vocalic data. Vowel positions mean values are at the mean with arrows indicating loadings. Loadings are multiplied by the standard deviation, by vowel, of the initial input data. This is OK for getting a quick, intuitive, interpretation of what the PCs mean in the vowel space. When using a model-to-PCA pipeline, it is not recommended to use these plots directly in publications as the models should more reliably control variation in vocalic readings than taking the standard mean and standard deviation.

Usage

plot_pc_vs(vowel_data, pca_obj, pc_no = 1, is_sig = FALSE)

Arguments

vowel_data

A dataframe whose first four columns are speaker ids, vowel ids, F1 values, and F2 values.

pca_obj

The result of a call to prcomp(), princomp() or pca_test().

pc_no

An integer, indicating which PC to plot (default is PC1).

is_sig

A boolean, indicating whether only 'significant' loadings, according to pca_test should be plotted (only works with objects of class pca_test_results).

Value

a ggplot object.

Examples

  onze_pca <- prcomp(onze_intercepts |> dplyr::select(-speaker), scale=TRUE)
  # Default is to plot PC1
  plot_pc_vs(onze_vowels, onze_pca)

  # Or plot another PC with `pc_no`
  plot_pc_vs(onze_vowels, onze_pca, pc_no = 3)