RMixtCompUtilities4.1.6 package

Available models

Add the missing element to algo parameter

Discriminative power

Similarity

Convert a MixtComp functional string into a list of 2 vectors

Create algo object

Create a functional in MixtComp format

Format the data parameter required by rmc

Format the model parameter

Get criterion value

Get the completed data from MixtComp object

Get the tik

Get the mixture density

Get the estimated parameter

Get the estimated class from MixtComp object

Names and Types Getters

Heatmap of the similarities between classes about clustering

Heatmap of the tik = P(Z_i=k|x_i)

Heatmap of the similarities between variables about clustering

Histogram of the misclassification probabilities

Plot of a MixtComp object

Convergence of algorithm

Boxplot per class

Mean and 95%-level confidence intervals per class

Barplot of the discriminative power of the classes

Barplot of the discriminative power of the variables

Evolution of parameters

Plot the mixture's proportions

Print Values

Rename a categorical value

RMixtCompUtilities

MixtComp Object Summaries