Scree plot for principal component importance — pca_plot

Displays the proportion of variance explained by the leading principal components. The function caps the number of displayed components to keep the visualization legible on very high-dimensional problems.

Usage

pca_plot_scree(
  pca_result,
  max_components = 25L,
  cumulative = TRUE,
  draw = TRUE,
  ...
)

Arguments

pca_result: A list created by pca_bigmatrix() or pca_stream_bigmatrix() containing standard deviation and explained variance elements.
max_components: Maximum number of components to display. Defaults to 25 or the available number of components, whichever is smaller.
cumulative: Logical flag indicating whether to overlay the cumulative explained variance line.
draw: Logical; set to FALSE to return the prepared data without drawing a plot (useful for testing).
...: Additional parameters passed to plot().

Value

A list with component, explained, and cumulative vectors is returned invisibly. When draw = TRUE, the function produces a scree plot using base graphics.