Package: statGraph 1.0.6
statGraph: Statistical Methods for Graphs
Contains statistical methods to analyze graphs, such as graph parameter estimation, model selection based on the Graph Information Criterion, statistical tests to discriminate two or more populations of graphs, correlation between graphs, and clustering of graphs. References: Takahashi et al. (2012) <doi:10.1371/journal.pone.0049949>, Fujita et al. (2017) <doi:10.3389/fnins.2017.00066>, Fujita et al. (2017) <doi:10.1016/j.csda.2016.11.016>, Fujita et al. (2019) <doi:10.1093/comnet/cnz028>.
Authors:
statGraph_1.0.6.tar.gz
statGraph_1.0.6.zip(r-4.7-any)statGraph_1.0.6.zip(r-4.6-any)statGraph_1.0.6.zip(r-4.5-any)
statGraph_1.0.6.tgz(r-4.6-any)statGraph_1.0.6.tgz(r-4.5-any)
statGraph_1.0.6.tar.gz(r-4.7-any)statGraph_1.0.6.tar.gz(r-4.6-any)
statGraph_1.0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
statGraph/json (API)
| # Install 'statGraph' in R: |
| install.packages('statGraph', repos = c('https://andrefujita.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:5221007b3c. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 117 | ||
| source / vignettes | OK | 154 | ||
| linux-release | OK | 117 | ||
| macos-release | OK | 140 | ||
| macos-oldrel | OK | 171 | ||
| windows-devel | OK | 97 | ||
| windows-release | OK | 61 | ||
| windows-oldrel | OK | 73 | ||
| wasm-release | OK | 83 |
Exports:anogvaGICgraph.acfgraph.cemgraph.cor.testgraph.distgraph.entropygraph.hclustgraph.kmeansgraph.model.selectiongraph.mult.scalinggraph.param.estimatorgraph.spectral.densitygraph.takahashi.testsp.anogva
Dependencies:cliclustercodetoolscpp11doParallelforeachglueigraphiteratorslatticelifecyclemagrittrMASSMatrixmvtnormpkgconfigrARPACKRcppRcppEigenrlangRSpectravctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Analysis Of Graph Variability (ANOGVA) | anogva |
| Graph Information Criterion (GIC) | GIC |
| Autocorrelation Function Estimation for Graphs | graph.acf |
| Graph Clustering Expectation-Maximization (gCEM) | graph.cem |
| Test for Association / Correlation Between Paired Samples of Graphs | graph.cor.test |
| Distance Matrix on a List of Graphs | graph.dist |
| Graph Spectral Entropy | graph.entropy |
| Hierarchical Cluster Analysis on a List of Graphs | graph.hclust |
| K-means for Graphs | graph.kmeans |
| Graph Model Selection | graph.model.selection |
| Multidimensional Scaling of Graphs | graph.mult.scaling |
| Graph Parameter Estimator | graph.param.estimator |
| Graph Spectral Density | graph.spectral.density |
| Test for the Jensen-Shannon Divergence Between Graphs | graph.takahashi.test |
| Semi-parametric Analysis of Graph Variability (SP-ANOGVA) | sp.anogva |