maage: Måge plot

In multiblock: Multiblock Data Fusion in Statistics and Machine Learning

Måge plot

Description

Måge plot for SO-PLS (sopls) cross-validation visualisation.

Usage

maage(
  object,
  expl_var = TRUE,
  pure.trace = FALSE,
  pch = 20,
  xlab = "# components",
  ylab = ifelse(expl_var, "Explained variance (%)", "RMSECV"),
  xlim = NULL,
  ylim = NULL,
  cex.text = 0.8,
  ...
)

maageSeq(
  object,
  compSeq = TRUE,
  expl_var = TRUE,
  pch = 20,
  xlab = "# components",
  ylab = ifelse(expl_var, "Explained variance (%)", "RMSECV"),
  xlim = NULL,
  ylim = NULL,
  cex.text = 0.8,
  col = "gray",
  col.block = c("red", "blue", "darkgreen", "purple", "black", "red", "blue",
    "darkgreen"),
  ...
)

Arguments

object	An SO-PLS model (sopls object)
expl_var	Logical indicating if explained variance (default) or RMSECV should be displayed.
pure.trace	Logical indicating if single block solutions should be traced in the plot.
pch	Scalar or symbol giving plot symbol.
xlab	Label for x-axis.
ylab	Label for y-axis.
xlim	Plot limits for x-axis (numeric vector).
ylim	Plot limits for y-axis (numeric vector).
cex.text	Text scaling (scalar) for better readability of plots.
...	Additional arguments to plot.
compSeq	Integer vector giving the sequence of previous components chosen for maageSeq (see example).
col	Line colour in plot.
col.block	Line colours for blocks (default = c('red','blue','darkgreen','purple','black'))

Details

This function can either be used for global optimisation across blocks or sequential optimisation, using maageSeq. The examples below show typical usage.

Value

The maage plot has no return.

See Also

Overviews of available methods, multiblock, and methods organised by main structure: basic, unsupervised, asca, supervised and complex.

Examples

data(wine)
ncomp <- unlist(lapply(wine, ncol))[-5]
so.wine <- sopls(`Global quality` ~ ., data=wine, ncomp=ncomp, 
            max_comps=10, validation="CV", segments=10)
maage(so.wine)

# Sequential search for optimal number of components per block
old.par <- par(mfrow=c(2,2), mar=c(3,3,0.5,1), mgp=c(2,0.7,0))
maageSeq(so.wine)
maageSeq(so.wine, 2)
maageSeq(so.wine, c(2,1))
maageSeq(so.wine, c(2,1,1))
par(old.par)

multiblock documentation built on April 4, 2025, 2:20 a.m.