mixOmics: plot.perf.pls – R documentation

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plot.perf.pls

Plot for model performance for PLS analyses

Description

Function to plot performance criteria, such as MSEP, RMSEP, R^2, Q^2 for s/PLS methods as a function of the number of components.

Usage

## S3 method for class 'perf.pls.mthd'
plot(
  x,
  criterion = "MSEP",
  xlab = "Number of components",
  ylab = NULL,
  LimQ2 = 0.0975,
  LimQ2.col = "grey30",
  sd = NULL,
  pch = 1,
  pch.size = 3,
  cex = 1.2,
  col = color.mixo(1),
  title = NULL,
  ...
)

## S3 method for class 'perf.spls.mthd'
plot(
  x,
  criterion = "MSEP",
  xlab = "Number of components",
  ylab = NULL,
  LimQ2 = 0.0975,
  LimQ2.col = "grey30",
  sd = NULL,
  pch = 1,
  pch.size = 3,
  cex = 1.2,
  col = color.mixo(1),
  title = NULL,
  ...
)

Arguments

`x`	an `perf.pls` object.
`criterion`	character string. What type of validation criterion to plot for `pls` or `spls`. One of `"MSEP"`, `"RMSEP"`, `"R2"` or `"Q2"`. More measures available for pls2 methods. See `perf`.
`xlab, ylab`	titles for x and y axes. Typically character strings, but can be expressions (e.g., `expression(R^2)`).
`LimQ2`	numeric value. Signification limit for the components in the model. Default is `LimQ2 = 0.0975`.
`LimQ2.col`	character string specifying the color for the `LimQ2` line to be plotted. If `"none"` the line will not be plotted.
`sd`	If 'nrepeat' was used in the call to 'perf', error bar shows the standard deviation if sd=TRUE. For mint objects sd is set to FALSE as the number of repeats is 1.
`pch`	Plot character to use.
`pch.size`	Plot character size to use.
`cex`	A numeric which adjusts the font size in the plot.
`col`	Character. Colour to be used for data points.
`title`	Character, Plot title. Not used by PLS2 feature-wise measure plots.
`...`	Not used.

Details

plot.perf creates one plot for each response variable in the model, laid out in a multi-panel display. See ?perf for examples.

Value

none

Author(s)

Al J Abadi

References

Rohart F, Gautier B, Singh A, Lê Cao K-A. mixOmics: an R package for 'omics feature selection and multiple data integration. PLoS Comput Biol 13(11): e1005752