plotDataBoxplot: Boxplot per class

In RMixtCompUtilities: Utility Functions for 'MixtComp' Outputs

Boxplot per class

Description

Display a boxplot (5

Usage

plotDataBoxplot(
  output,
  var,
  class = seq_len(output$algo$nClass),
  grl = TRUE,
  pkg = c("ggplot2", "plotly"),
  ...
)

Arguments

output	object returned by mixtCompLearn function from RMixtComp or rmcMultiRun function from RMixtCompIO
var	name of the variable
class	classes to plot
grl	if TRUE plot the general distribution of the data
pkg	"ggplot2" or "plotly". Package used to plot
...	other parameters (see Details)

Details

For functional data, three other parameters are available:

add.obs

if TRUE, observations are added to the plot. Default = FALSE.

ylim

ylim of the plot.

xlim

xlim of the plot.

Author(s)

Matthieu MARBAC

See Also

Other plot: heatmapClass(), heatmapTikSorted(), heatmapVar(), histMisclassif(), plot.MixtComp(), plotConvergence(), plotDataCI(), plotDiscrimClass(), plotDiscrimVar(), plotParamConvergence(), plotProportion()

Examples

if (requireNamespace("RMixtCompIO", quietly = TRUE)) {
  dataLearn <- list(
    var1 = as.character(c(rnorm(50, -2, 0.8), rnorm(50, 2, 0.8))),
    var2 = as.character(c(rnorm(50, 2), rpois(50, 8)))
  )

  model <- list(
    var1 = list(type = "Gaussian", paramStr = ""),
    var2 = list(type = "Poisson", paramStr = "")
  )

  algo <- list(
    nClass = 2,
    nInd = 100,
    nbBurnInIter = 100,
    nbIter = 100,
    nbGibbsBurnInIter = 100,
    nbGibbsIter = 100,
    nInitPerClass = 3,
    nSemTry = 20,
    confidenceLevel = 0.95,
    ratioStableCriterion = 0.95,
    nStableCriterion = 10,
    mode = "learn"
  )

  resLearn <-RMixtCompIO::rmcMultiRun(algo, dataLearn, model, nRun = 3)

  # plot
  plotDataBoxplot(resLearn, "var1")
}

RMixtCompUtilities documentation built on Sept. 22, 2023, 5:10 p.m.