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clustAnalytics (version 0.5.5)

Cluster Evaluation on Graphs

Description

Evaluates the stability and significance of clusters on 'igraph' graphs. Supports weighted and unweighted graphs. Implements the cluster evaluation methods defined by Arratia A, Renedo M (2021) . Also includes an implementation of the Reduced Mutual Information introduced by Newman et al. (2020) .

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Install

install.packages('clustAnalytics')

Monthly Downloads

244

Version

0.5.5

License

GPL (>= 3)

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0

Stars

5

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Maintainer

Martc3<ad> Mirambell

Last Published

February 18th, 2024

Functions in clustAnalytics (0.5.5)

clustAnalytics-package

clustAnalytics: Cluster Evaluation on Graphs
average_odf

Average Out Degree Fraction
average_degree

Average Degree
log_omega_estimation

Approximation of log(omega(a,b))
internal_density

Internal Density
weighted_transitivity

Weighed transitivity of a weighted graph.
edges_inside

Edges Inside
estimate_H_fractions

Estimates |H_i|/|H_{i+1}| for the first r rows
estimate_H_fraction_r_rows

Estimates |H_0|/|H_r*|
c_rs_table

Contingency table from membership vectors
density_ratio

Density Ratio
cut_ratio

Cut Ratio
apply_subgraphs

Applies function to each subgraph of a graph
conductance

Conductance
g_forex

Forex correlation network
count_contingency_tables_log

Natural logarithm of the number of contingency tables
evaluate_significance

Evaluates significance of cluster algorithm results on a graph
rewireCpp

Randomizes a weighted graph while keeping the degree distribution constant.
contingency_to_membership_vectors

Computes possible membership vectors from contingency table
scoring_functions

Scoring Functions of a Graph Partition
igraph_to_edgelist

Returns edgelist with weights from a weighted igraph graph
make_graph_weighted

Make graph weighted
max_odf

Max Out Degree Fraction
walk_step

Performs a step of the Markov Chain Monte Carlo method
evaluate_significance_r

Evaluates the significance of a graph's clusters
weighted_clustering_coefficient

Weighted clustering coefficient of a weighted graph.
expansion

Expansion
reduced_mutual_information

Reduced Mutual Information
coverage

Coverage
normalized_cut

Normalized cut
out_degree_fractions

Maximum, Average, and Flake Out Degree Fractions of a Graph Partition
triangle_participation_ratio_communities

Triangle Participation Ratio (community-wise)
relabel

Relabels membership vector
sort_matrix

Sort matrix
boot_alg_list

Performs nonparametric bootstrap to a graph and a list of clustering algorithms
barabasi_albert_blocks

Generates a Barabási-Albert graph with community structure
FOMD

FOMD (Fraction Over Median Degree)
auxiliary_functions

Auxiliary Functions of a Graph Partition
H_fractions_rows

Estimates |H_i|/|H_(i+1)| for the first n_rows rows