RMixtCompUtilities (version 4.1.3)

plotParamConvergence: 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

See Also

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

Examples

# NOT RUN {
require(RMixtCompIO) # for learning a mixture model
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 <- rmcMultiRun(algo, dataLearn, model, nRun = 3)

# plot
plotParamConvergence(resLearn, "var1")
plotParamConvergence(resLearn, "var2")


# }