RMixtCompUtilities (version 4.1.3)

getType: 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.

See Also

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

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)

# get type
type <- getType(resLearn)

# get model object
model <- getModel(resLearn)

# get variable names
varNames <- getVarNames(resLearn)


# }