RMixtCompUtilities-package |
RMixtCompUtilities |
availableModels |
Available models |
completeAlgo |
Add the missing element to algo parameter |
computeDiscrimPowerClass |
Discriminative power |
computeDiscrimPowerVar |
Discriminative power |
computeSimilarityClass |
Similarity |
computeSimilarityVar |
Similarity |
convertFunctionalToVector |
Convert a MixtComp functional string into a list of 2 vectors |
createAlgo |
Create algo object |
createFunctional |
Create a functional in MixtComp format |
formatData |
Format the data parameter required by rmc |
formatModel |
Format the model parameter |
getBIC |
Get criterion value |
getCompletedData |
Get the completed data from MixtComp object |
getEmpiricTik |
Get the tik |
getICL |
Get criterion value |
getMixtureDensity |
Get the mixture density |
getModel |
Names and Types Getters |
getParam |
Get the estimated parameter |
getPartition |
Get the estimated class from MixtComp object |
getProportion |
Get the estimated parameter |
getTik |
Get the tik |
getType |
Names and Types Getters |
getVarNames |
Names and Types Getters |
heatmapClass |
Heatmap of the similarities between classes about clustering |
heatmapTikSorted |
Heatmap of the tik = P(Z_i=k|x_i) |
heatmapVar |
Heatmap of the similarities between variables about clustering |
histMisclassif |
Histogram of the misclassification probabilities |
plot.MixtComp |
Plot of a _MixtComp_ object |
plotConvergence |
Convergence of algorithm |
plotDataBoxplot |
Boxplot per class |
plotDataCI |
Mean and 95%-level confidence intervals per class |
plotDiscrimClass |
Barplot of the discriminative power of the classes |
plotDiscrimVar |
Barplot of the discriminative power of the variables |
plotParamConvergence |
Evolution of parameters |
plotProportion |
Plot the mixture's proportions |
print.MixtComp |
Print Values |
refactorCategorical |
Rename a categorical value |
summary.MixtComp |
MixtComp Object Summaries |