getType {RMixtCompUtilities}

Names and Types Getters

Description

getType returns the type output of a MixtComp object, getModel returns the model object, getVarNames returns the name for each variable

Usage

getType(outMixtComp, with.z_class = FALSE)

getModel(outMixtComp, with.z_class = FALSE)

getVarNames(outMixtComp, with.z_class = FALSE)

Arguments

outMixtComp

object of class MixtCompLearn or MixtComp obtained using mixtCompLearn or mixtCompPredict functions from RMixtComp package or rmcMultiRun from RMixtCompIO package.

with.z_class

if TRUE, the type of z_class is returned.

Value

a vector containing the type of models, names associated with each individual.

Author(s)

Quentin Grimonprez

See Also

Other getter: getBIC(), getCompletedData(), getEmpiricTik(), getMixtureDensity(), getParam(), getPartition()

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)

  # get type
  type <- getType(resLearn)

  # get model object
  model <- getModel(resLearn)

  # get variable names
  varNames <- getVarNames(resLearn)
}