Scatterplot matrix of effect matrices scores — lmpScoreScatterPlotM • limpca

Plots the scores of all model effects simultaneously in a scatterplot matrix. By default, the first PC only is kept for each model effect and, as a wrapper of plotScatterM, the choice of symbols and colors to distinguish factor levels allows an enriched visualization of the factors’ effect on the responses.

Usage

lmpScoreScatterPlotM(
  resLmpPcaEffects,
  effectNames = NULL,
  PCdim = NULL,
  modelAbbrev = FALSE,
  ...
)

Arguments

resLmpPcaEffects: A list corresponding to the output value of lmpPcaEffects.
effectNames: A character vector with the name of the effects to plot.
PCdim: A numeric vector with the same length than effectNames and indicating the number of component to plot.
modelAbbrev: A logical whether to abbreviate the interaction terms or not.
...: Additional arguments to be passed to plotScatterM.

Value

A matrix of graphs

Details

lmpScoreScatterPlotM is a wrapper of plotScatterM.

Examples


data("UCH")
resLmpModelMatrix <- lmpModelMatrix(UCH)
ResLmpEffectMatrices <- lmpEffectMatrices(resLmpModelMatrix)
resLmpPcaEffects <- lmpPcaEffects(ResLmpEffectMatrices, method = "ASCA-E")

lmpScoreScatterPlotM(resLmpPcaEffects,
  varname.colorup = "Citrate",
  varname.pchup = "Hippurate",
  varname.pchdown = "Day",
  varname.colordown = "Time"
)


# advanced setting
lmpScoreScatterPlotM(resLmpPcaEffects,
  modelAbbrev = FALSE,
  effectNames = c("Citrate", "Hippurate", "Hippurate:Citrate"),
  PCdim = c(2, 2, 2),
  varname.colorup = "Citrate",
  vec.colorup = c("red", "blue", "green"),
  varname.pchup = "Hippurate",
  vec.pchup = c(1, 2, 3),
  varname.pchdown = "Day",
  vec.pchdown = c(4, 5),
  varname.colordown = "Time",
  vec.colordown = c("brown", "grey")
)