RMixtCompUtilities (version 4.1.6)

heatmapTikSorted: Heatmap of the tik = P(Z_i=k|x_i)

Description

Heatmap of the tik = P(Z_i=k|x_i)

Usage

heatmapTikSorted(output, pkg = c("ggplot2", "plotly"), ...)

Arguments

output

object returned by mixtCompLearn function from RMixtComp or rmcMultiRun function from RMixtCompIO

pkg

"ggplot2" or "plotly". Package used to plot

...

arguments to be passed to plot_ly

Author

Matthieu MARBAC

Details

Observation are sorted according to the hard partition then for each component they are sorted by decreasing order of their tik's

See Also

getTik

Other plot: heatmapClass(), heatmapVar(), histMisclassif(), plot.MixtComp(), plotConvergence(), plotDataBoxplot(), 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
  heatmapTikSorted(resLearn)
}