Package: nevada 0.2.0

Aymeric Stamm

nevada: Network-Valued Data Analysis

A flexible statistical framework for network-valued data analysis. It leverages the complexity of the space of distributions on graphs by using the permutation framework for inference as implemented in the 'flipr' package. Currently, only the two-sample testing problem is covered and generalization to k samples and regression will be added in the future as well. It is a 4-step procedure where the user chooses a suitable representation of the networks, a suitable metric to embed the representation into a metric space, one or more test statistics to target specific aspects of the distributions to be compared and a formula to compute the permutation p-value. Two types of inference are provided: a global test answering whether there is a difference between the distributions that generated the two samples and a local test for localizing differences on the network structure. The latter is assumed to be shared by all networks of both samples. References: Lovato, I., Pini, A., Stamm, A., Vantini, S. (2020) "Model-free two-sample test for network-valued data" <doi:10.1016/j.csda.2019.106896>; Lovato, I., Pini, A., Stamm, A., Taquet, M., Vantini, S. (2021) "Multiscale null hypothesis testing for network-valued data: Analysis of brain networks of patients with autism" <doi:10.1111/rssc.12463>.

Authors:Ilenia Lovato [aut], Alessia Pini [aut], Aymeric Stamm [aut, cre], Simone Vantini [aut]

nevada_0.2.0.tar.gz
nevada_0.2.0.tar.gz(r-4.5-noble)nevada_0.2.0.tar.gz(r-4.4-noble)
nevada_0.2.0.tgz(r-4.4-emscripten)nevada_0.2.0.tgz(r-4.3-emscripten)
nevada.pdf |nevada.html
nevada/json (API)
NEWS

# Install 'nevada' in R:
install.packages('nevada', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/astamm/nevada/issues

Pkgdown:https://astamm.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

openblascpp

2.70 score 3 scripts 177 downloads 1 mentions 35 exports 88 dependencies

Last updated 1 years agofrom:308e2ee20e. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 28 2024
R-4.5-linux-x86_64OKNov 28 2024

Exports:%>%as_nvdas_vertex_partitiondist_frobeniusdist_hammingdist_nvddist_root_euclideandist_spectraledge_count_global_variablesgenerate_sigma_algebraipro_frobeniusnvdpower2rbinom_networkrepr_adjacencyrepr_graphonrepr_laplacianrepr_modularityrepr_nvdrexp_networkrpois_networkrsbmsample2_sbmstat_generalized_edge_countstat_original_edge_countstat_student_euclideanstat_weighted_edge_countstat_welch_euclideansubgraph_fullsubgraph_intersubgraph_intratest2_globaltest2_localvar_nvdvar2_nvd

Dependencies:askpassclicliprcodetoolscolorspacecpp11crayoncredentialscurldescdialsDiceDesigndigestdplyrfansifarverfliprforcatsfsfurrrfuturegenericsgertggplot2ghgitcredsglobalsgluegtablehardhatherehttr2igraphiniisobandjsonlitelabelinglatticelifecyclelistenvmagrittrMASSMatrixmgcvmunsellnlmeopenssloptimParallelparallellypbapplypillarpkgconfigpngpurrrR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppTOMLRdpackreticulatergenoudrgeomstatsrlangrprojrootRSpectrarstudioapiscalessfdstringistringrsystibbletidyrtidyselecttsneumapusethisutf8vctrsviridisLitewhiskerwithryamlzip

Network-Valued Data Analysis

Rendered fromnevada.Rmdusingknitr::rmarkdownon Nov 28 2024.

Last update: 2023-09-03
Started: 2021-09-25

Readme and manuals

Help Manual

Help pageTopics
Coercion to Network-Valued Data Objectas_nvd
Coercion to Vertex Partitionas_vertex_partition
Pairwise Distance Matrix Between Two Samples of Networksdist_nvd
Distances Between Networksdistances dist_frobenius dist_hamming dist_root_euclidean dist_spectral
Transform distance matrix in edge properties of minimal spanning treeedge_count_global_variables
Sigma-Algebra generated by a Partitiongenerate_sigma_algebra
Inner-Products Between Networksinner-products ipro_frobenius
Fréchet Mean of Network-Valued Datamean.nvd
Network-Valued Data Constructornvd
MDS Visualization of Network Distributionsautoplot.nvd nvd-plot plot.nvd
Power Simulations for Permutation Testspower2
Network-Valued to Matrix-Valued Datarepr_nvd
Network Representation Functionsrepresentations repr_adjacency repr_graphon repr_laplacian repr_modularity
Two-Sample Stochastic Block Model Generatorsample2_sbm
Graph samplers using edge distributionsrbinom_network rexp_network rpois_network rsbm samplers
Test Statistics for Network Populationsstatistics stat_generalized_edge_count stat_original_edge_count stat_student_euclidean stat_weighted_edge_count stat_welch_euclidean
Full, intra and inter subgraph generatorssubgraphs subgraph_full subgraph_inter subgraph_intra
Global Two-Sample Test for Network-Valued Datatest2_global
Local Two-Sample Test for Network-Valued Datatest2_local
Fréchet Variance of Network-Valued Data Around a Given Networkvar_nvd
Fréchet Variance of Network-Valued Data from Inter-Point Distancesvar2_nvd