R: Clustering and Model Selection with the Integrated Classification Likelihood

# Clustering and Model Selection with the Integrated Classification Likelihood

## Documentation for package ‘greed’ version 0.6.2

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

A B C D E F G H I J K L M N P R S T Y

greed-package | Model based hierarchical clustering

## -- A --

Alg-class | Abstract optimization algorithm class
available_algorithms | Display the list of every currently available optimization algorithm
available_models | Display the list of every currently available DLVM

## -- B --

Books | Books about US politics network dataset

## -- C --

clustering | Method to extract the clustering results from an 'IclFit-class' object
clustering-method | Method to extract the clustering results from an 'IclFit-class' object
coef-method | Extract parameters from an 'DcLbmFit-class' object
coef-method | Extract parameters from an 'DcSbmFit-class' object
coef-method | Extract mixture parameters from 'DiagGmmFit-class' object
coef-method | Extract mixture parameters from 'GmmFit-class' object
coef-method | Extract parameters from an 'IclFit-class' object
coef-method | Extract parameters from an 'LcaFit-class' object
coef-method | Extract parameters from an 'MoMFit-class' object
coef-method | Extract mixture parameters from 'MoRFit-class' object using MAP estimation
coef-method | Extract parameters from an 'MultSbmFit-class' object
coef-method | Extract parameters from an 'SbmFit-class' object
CombinedModels | Combined Models classes
CombinedModels-class | Combined Models classes
CombinedModelsFit-class | Combined Models fit results class
CombinedModelsPath-class | Combined Models hierarchical fit results class
cut-method | Method to cut a DcLbmPath solution to a desired number of cluster
cut-method | Generic method to cut a path solution to a desired number of cluster

## -- D --

DcLbm | Degree Corrected Latent Block Model for bipartite graph class
DcLbm-class | Degree Corrected Latent Block Model for bipartite graph class
DcLbmFit-class | Degree corrected Latent Block Model fit results class
DcLbmPath-class | Degree corrected Latent Block Model hierarchical fit results class
DcLbmPrior | Degree Corrected Latent Block Model for bipartite graph class
DcLbmPrior-class | Degree Corrected Latent Block Model for bipartite graph class
DcSbm | Degree Corrected Stochastic Block Model Prior class
DcSbm-class | Degree Corrected Stochastic Block Model Prior class
DcSbmFit-class | Degree Corrected Stochastic Block Model fit results class
DcSbmPath-class | Degree Corrected Stochastic Block Model hierarchical fit results class
DcSbmPrior | Degree Corrected Stochastic Block Model Prior class
DcSbmPrior-class | Degree Corrected Stochastic Block Model Prior class
DiagGmm | Diagonal Gaussian Mixture Model Prior description class
DiagGmm-class | Diagonal Gaussian Mixture Model Prior description class
DiagGmmFit-class | Diagonal Gaussian mixture model fit results class
DiagGmmPath-class | Diagonal Gaussian mixture model hierarchical fit results class
DiagGmmPrior | Diagonal Gaussian Mixture Model Prior description class
DiagGmmPrior-class | Diagonal Gaussian Mixture Model Prior description class
DlvmCoPrior-class | Abstract class to represent a generative model for co-clustering
DlvmPrior-class | Abstract class to represent a generative model for clustering

## -- E --

extractSubModel | Extract a part of a 'CombinedModelsPath-class' object
extractSubModel-method | Extract a part of a 'CombinedModelsPath-class' object

## -- F --

fashion | Fashion mnist dataset
Fifa | Fifa data
Football | American College football network dataset

## -- G --

Genetic | Genetic optimization algorithm
Genetic-class | Genetic optimization algorithm
Gmm | Gaussian Mixture Model Prior description class
Gmm-class | Gaussian Mixture Model Prior description class
GmmFit-class | Gaussian mixture model fit results class
gmmpairs | Make a matrix of plots with a given data and gmm fitted parameters
GmmPath-class | Gaussian mixture model hierarchical fit results class
GmmPrior | Gaussian Mixture Model Prior description class
GmmPrior-class | Gaussian Mixture Model Prior description class
greed | Model based hierarchical clustering

## -- H --

H | Compute the entropy of a discrete sample
Hybrid | Hybrid optimization algorithm
Hybrid-class | Hybrid optimization algorithm

## -- I --

ICL | Generic method to extract the ICL value from an 'IclFit-class' object
ICL-method | Generic method to extract the ICL value from an 'IclFit-class' object
IclFit-class | Abstract class to represent a clustering result
IclPath-class | Abstract class to represent a hierarchical clustering result

## -- J --

Jazz | Jazz musicians network dataset

## -- K --

K | Generic method to get the number of clusters from an 'IclFit-class' object
K-method | Generic method to get the number of clusters from an 'IclFit-class' object

## -- L --

Lca | Latent Class Analysis Model Prior class
Lca-class | Latent Class Analysis Model Prior class
LcaFit-class | Latent Class Analysis fit results class
LcaPath-class | Latent Class Analysis hierarchical fit results class
LcaPrior | Latent Class Analysis Model Prior class
LcaPrior-class | Latent Class Analysis Model Prior class

## -- M --

MI | Compute the mutual information of two discrete samples
MoM | Mixture of Multinomial Model Prior description class
MoM-class | Mixture of Multinomial Model Prior description class
MoMFit-class | Mixture of Multinomial fit results class
MoMPath-class | Mixture of Multinomial hierarchical fit results class
MoMPrior | Mixture of Multinomial Model Prior description class
MoMPrior-class | Mixture of Multinomial Model Prior description class
MoR | Multivariate mixture of regression Prior model description class
MoR-class | Multivariate mixture of regression Prior model description class
MoRFit-class | Clustering with a multivariate mixture of regression model fit results class
MoRPath-class | Multivariate mixture of regression model hierarchical fit results class
MoRPrior | Multivariate mixture of regression Prior model description class
MoRPrior-class | Multivariate mixture of regression Prior model description class
Multistarts | Greedy algorithm with multiple start class
Multistarts-class | Greedy algorithm with multiple start class
MultSbm | Multinomial Stochastic Block Model Prior class
MultSbm-class | Multinomial Stochastic Block Model Prior class
MultSbmFit-class | Multinomial Stochastic Block Model fit results class
MultSbmPath-class | Multinomial Stochastic Block Model hierarchical fit results class
MultSbmPrior | Multinomial Stochastic Block Model Prior class
MultSbmPrior-class | Multinomial Stochastic Block Model Prior class
mushroom | Mushroom data

## -- N --

Ndrangheta | Ndrangheta mafia covert network dataset
NewGuinea | NewGuinea data
NMI | Compute the normalized mutual information of two discrete samples

## -- P --

plot-method | Plot a 'DcLbmFit-class'
plot-method | Plot a 'DcLbmPath-class'
plot-method | Plot a 'DcSbmFit-class' object
plot-method | Plot a 'DiagGmmFit-class' object
plot-method | Plot a 'GmmFit-class' object
plot-method | Plot an 'IclPath-class' object
plot-method | Plot a 'LcaFit-class' object
plot-method | Plot a 'MoMFit-class' object
plot-method | Plot a 'MultSbmFit-class' object
plot-method | Plot a 'SbmFit-class' object
prior | Generic method to extract the prior used to fit 'IclFit-class' object
prior-method | Generic method to extract the prior used to fit 'IclFit-class' object

## -- R --

rdcsbm | Generates graph adjacency matrix using a degree corrected SBM
rlbm | Generate a data matrix using a Latent Block Model
rlca | Generate data from lca model
rmm | Generate data using a Multinomial Mixture
rmreg | Generate data from a mixture of regression model
rmultsbm | Generate a graph adjacency matrix using a Stochastic Block Model
rsbm | Generate a graph adjacency matrix using a Stochastic Block Model

## -- S --

Sbm | Stochastic Block Model Prior class
Sbm-class | Stochastic Block Model Prior class
SbmFit-class | Stochastic Block Model fit results class
SbmPath-class | Stochastic Block Model hierarchical fit results class
SbmPrior | Stochastic Block Model Prior class
SbmPrior-class | Stochastic Block Model Prior class
Seed | Greedy algorithm with seeded initialization
Seed-class | Greedy algorithm with seeded initialization
SevenGraders | SevenGraders data
show-method | Show an IclPath object
spectral | Regularized spectral clustering

## -- T --

to_multinomial | Convert a binary adjacency matrix with missing value to a cube

## -- Y --

Youngpeoplesurvey | Young People survey data