statnetWeb

This is an R-shiny interface for the statnet suite of R packages. It currently incorporates functionality from the ergm, network and sna packages, allowing users to fit and assess exponential random graph models via GUI.

Run the app in two ways:

• Through the shinyapps server with this link: https://statnet.shinyapps.io/statnetWeb
• On your own machine using the statnetWeb R package:

install.packages("statnetWeb")
statnetWeb::run_sw()

statnetWeb wiki:
https://statnet.csde.washington.edu/trac/wiki/statnetWeb

statnet wiki:
https://statnet.csde.washington.edu/trac

statnet packages on CRAN:
http://cran.r-project.org/web/packages/ergm/
http://cran.r-project.org/web/packages/network/
http://cran.r-project.org/web/packages/sna/

New in v0.3.4

• Conditional uniform graph test histograms in Network Descriptives
• Descriptions of built-in networks
• Minor bug fixes

New in v0.3.3

• Fix bug from v0.3.2 preventing built-in networks from loading
• Prevent calls to search.ergmTerms() from printing to the console

New in v0.3.2

• App is compatible with Shiny v0.11.1.9002 (we have a new look!)
• Only .rds files supported when saving and uploading from the R environment.
• Issue solved where GOF plots from directed networks were not appearing.
• Issue with uploading edge values solved.

New in v0.3.1

• Improved method of saving user-entered attributes
• Bug in uploading relational data saved as R object is fixed
• "Fit Model" button is closer to summary statistics
• User can add terms to formula by pressing Enter key
• User is not allowed to color code degree distribution of total degree for directed networks (in- and out-degree distributions are allowed)
• Title of application is incorporated into title of first tab
• Prevented error in viewing GOF comparison when no models are saved
• New color palettes for attributes with more than nine levels

New in v0.3.0

• Access term documentation within Fit Model page
• Customize MCMC control parameters when fitting a model or simulating from a model
• Save up to five different models for a single network
• Compare coefficients and AIC/BIC scores across models
• Switch between models when looking at MCMC Diagnostics, GOF and Simulations
• Compare GOF plots across saved models in a comprehensive chart
• Plot simulation statistics compared to target statistics
• Arrow icons for page navigation