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 |