plotDiscriminationPower.simcam: Discrimination power plot for SIMCAM model

In mdatools: Multivariate Data Analysis for Chemometrics

Discrimination power plot for SIMCAM model

Description

Shows a plot with discrimination power of predictors for a pair of SIMCA models

Usage

## S3 method for class 'simcam'
plotDiscriminationPower(
  obj,
  nc = c(1, 2),
  type = "h",
  main = paste0("Discrimination power: ", obj$classnames[nc[1]], " vs. ",
    obj$classname[nc[2]]),
  xlab = attr(obj$dispower, "xaxis.name"),
  ylab = "",
  ...
)

Arguments

obj	a SIMCAM model (object of class simcam)
nc	vector with two values - classes (SIMCA models) to show the plot for
type	type of the plot
main	main plot title
xlab	label for x axis
ylab	label for y axis
...	other plot parameters (see mdaplotg for details)

Details

Discrimination power shows an ability of variables to separate classes. The power is computed similar to model distance, using variance of residuals. However in this case instead of sum the variance across all variables, we take the ratio separately for individual variables.

Discrimination power equal or above 3 is considered as high.

mdatools documentation built on Sept. 11, 2024, 7:59 p.m.