plotScores.pca: Scores plot for PCA model

In svkucheryavski/mdatools: Multivariate Data Analysis for Chemometrics

Scores plot for PCA model

Description

Shows a scores plot for selected components.

Usage

## S3 method for class 'pca'
plotScores(
  obj,
  comp = if (obj$ncomp > 1) c(1, 2) else 1,
  type = "p",
  show.axes = TRUE,
  show.legend = TRUE,
  res = obj$res,
  ...
)

Arguments

obj	a PCA model (object of class pca)
comp	a value or vector with several values - number of components to show the plot for
type	type of the plot ("p", "l", "b", "h")
show.axes	logical, show or not a axes lines crossing origin (0,0)
show.legend	logical, show or not a legend on the plot
res	list with result objects to show the variance for
...	other plot parameters (see mdaplotg for details)

Details

If plot is created only for one result object (e.g. calibration set), then the behaviour and all settings for the scores plot are identical to plotScores.ldecomp. In this case you can show scores as a scatter, line or bar plot for any number of components.

Otherwise (e.g. if model contains results for calibration and test set) the plot is a group plot created using mdaplotg method and only scatter plot can be used.

See examples in help for pca function.

svkucheryavski/mdatools documentation built on Aug. 25, 2023, 12:27 p.m.