View source: R/MIXTCOMP_getter.R
getEmpiricTik | R Documentation |
Get the a posteriori probability to belong to each class for each individual
getEmpiricTik(outMixtComp)
getTik(outMixtComp, log = TRUE)
outMixtComp |
object of class MixtCompLearn or MixtComp obtained using |
log |
if TRUE, log(tik) are returned |
getTik returns a posteriori probabilities computed with the returned parameters. getEmpiricTik returns an estimation based on the sampled z_i during the algorithm.
a matrix containing the tik for each individual (in row) and each class (in column).
Quentin Grimonprez
heatmapTikSorted
Other getter:
getBIC()
,
getCompletedData()
,
getMixtureDensity()
,
getParam()
,
getPartition()
,
getType()
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 tik
tikEmp <- getEmpiricTik(resLearn)
tik <- getTik(resLearn, log = FALSE)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.