Package: epinet 2.1.11
epinet: Epidemic/Network-Related Tools
A collection of epidemic/network-related tools. Simulates transmission of diseases through contact networks. Performs Bayesian inference on network and epidemic parameters, given epidemic data.
Authors:
epinet_2.1.11.tar.gz
epinet_2.1.11.zip(r-4.5)epinet_2.1.11.zip(r-4.4)epinet_2.1.11.zip(r-4.3)
epinet_2.1.11.tgz(r-4.4-x86_64)epinet_2.1.11.tgz(r-4.4-arm64)epinet_2.1.11.tgz(r-4.3-x86_64)epinet_2.1.11.tgz(r-4.3-arm64)
epinet_2.1.11.tar.gz(r-4.5-noble)epinet_2.1.11.tar.gz(r-4.4-noble)
epinet_2.1.11.tgz(r-4.4-emscripten)epinet_2.1.11.tgz(r-4.3-emscripten)
epinet.pdf |epinet.html✨
epinet/json (API)
| # Install 'epinet' in R: |
| install.packages('epinet', repos = c('https://cgroendyke.r-universe.dev', 'https://cloud.r-project.org')) |
- HagellochDyadCov - Hagelloch measles data.
- HagellochTimes - Hagelloch measles data.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:f953dbac45. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 08 2024 |
| R-4.5-win-x86_64 | OK | Sep 08 2024 |
| R-4.5-linux-x86_64 | OK | Sep 08 2024 |
| R-4.4-win-x86_64 | OK | Sep 08 2024 |
| R-4.4-mac-x86_64 | OK | Sep 08 2024 |
| R-4.4-mac-aarch64 | OK | Sep 08 2024 |
| R-4.3-win-x86_64 | OK | Sep 08 2024 |
| R-4.3-mac-x86_64 | OK | Sep 08 2024 |
| R-4.3-mac-aarch64 | OK | Sep 08 2024 |
Exports:buildepifromoutputBuildXepi2newickepi2newick.intepi2newickmcmcepibayesmcmcepigraphmcmccepinetessetimestartvaluesitimestartvaluesMCMCcontrolplot.epidemicplot.epinetplotepitreeprint.epidemicprint.epinetpriorcontrolremovesusceptiblesSEIR.simulatorSimulateDyadicLinearERGMsummary.epidemicsummary.epinetwrite.epinet
Dependencies:clicodafansigluelatticelifecyclemagrittrnetworkpillarpkgconfigrlangstatnet.commontibbleutf8vctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Build a dyadic covariate matrix (X) | BuildX |
| Prints a transmission tree in Newick format. | epi2newick epi2newickmcmc |
| Uses epidemic data to perform Bayesian inference on a contact network | epibayesmcmc epinet |
| Calculate the Effective Sample Size | ess |
| Hagelloch measles data. | HagellochDyadCov HagellochTimes |
| Set control parameters for epinet MCMC algorithm | MCMCcontrol |
| Plot the spread of an epidemic | plot.epidemic |
| Plot the spread of an epidemic | plot.epinet |
| Prints an epidemict object | print.epidemic |
| Print basic information about an epinet object | print.epinet |
| Set prior distributions and hyperparameters for epinet MCMC algorithm | priorcontrol |
| Simulate an epidemic on a contact network | SEIR.simulator |
| Simulates an ERGM network using given covariate values | SimulateDyadicLinearERGM |
| Summarize simulated epidemic | summary.epidemic |
| Summarize posterior samples from epinet object | summary.epinet |
| Writes posterior samples from an epinet object to an output file | write.epinet |
