RMixtCompUtilities (version 4.1.3)

getEmpiricTik: Get the tik

Description

Get the a posteriori probability to belong to each class for each individual

Usage

getEmpiricTik(outMixtComp)
getTik(outMixtComp, log = TRUE)

Arguments

outMixtComp

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

log

if TRUE, log(tik) are returned

Value

a matrix containing the tik for each individuals (in row) and each class (in column).

Details

getTik returns a posteriori probabilities computed with the returned parameters. getEmpiricTik returns an estimation based on the sampled z_i during the algorithm.

See Also

heatmapTikSorted

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

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 tik
tikEmp <- getEmpiricTik(resLearn)
tik <- getTik(resLearn, log = FALSE)

# }