ClusVis-package: Gaussian-Based Visualization of Gaussian and Non-Gaussian...

Description Details Author(s) Examples

Description

The main function for parameter inference is clusvis. Moreover, specific functions for parameter inference clusvisMixmod are implemented to deal with model-based clustering done with R packages Rmixmod and Rmixcomp respectively. After parameter inference, visualization is done with function plotDensityClusVisu.

Details

Package: ClusVis
Type: Package
Version: 1.1.0
Date: 2018-04-18
License: GPL-3
LazyLoad: yes

Author(s)

Biernacki, C. and Marbac, M. and Vandewalle, V.

Examples

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## Not run: 
### Categorical data clustering with Rmixmod
# Package loading
require(Rmixmod)
 
# Data loading (categorical data)
data(birds)

# Model-based clustering with 3 components
resmixmod <- mixmodCluster(birds, 3)

# Inference of the parameters used for results visualization (general approach)
# Probabilities of classification are not sampled from the model parameter,
# but observed probabilities of classification are used for parameter estimation
resvisu <- clusvis(log(resmixmod@bestResult@proba),
                   resmixmod@bestResult@parameters@proportions)

# Inference of the parameters used for results visualization
# (specific for Rmixmod results)
# It is better because probabilities of classification are generated
# by using the model parameters
resvisu <- clusvisMixmod(resmixmod)

# Component interpretation graph
plotDensityClusVisu(resvisu)

# Scatter-plot of the observation memberships
plotDensityClusVisu(resvisu,  add.obs = TRUE)

## End(Not run)

ClusVis documentation built on April 19, 2018, 3:01 a.m.