plotParamConvergence: Evolution of parameters

In RMixtCompUtilities: Utility Functions for 'MixtComp' Outputs

Evolution of parameters

Description

Plot the evolution of estimated parameters after the burn-in phase.

Usage

plotParamConvergence(output, var, ...)

Arguments

output	object returned by mixtCompLearn function from RMixtComp or rmcMultiRun function from RMixtCompIO
var	name of the variable
...	graphical parameters

Author(s)

Quentin Grimonprez

See Also

Other plot: heatmapClass(), heatmapTikSorted(), heatmapVar(), histMisclassif(), plot.MixtComp(), plotConvergence(), plotDataBoxplot(), plotDataCI(), plotDiscrimClass(), plotDiscrimVar(), 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
  plotParamConvergence(resLearn, "var1")
  plotParamConvergence(resLearn, "var2")
}

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