plotDiscriminationPower.simcam {mdatools}

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.