Package: epichains 0.1.1.9000
James M. Azam
epichains: Simulating and Analysing Transmission Chain Statistics Using Branching Process Models
Provides methods to simulate and analyse the size and length of branching processes with an arbitrary offspring distribution. These can be used, for example, to analyse the distribution of chain sizes or length of infectious disease outbreaks, as discussed in Farrington et al. (2003) <doi:10.1093/biostatistics/4.2.279>.
Authors:
epichains_0.1.1.9000.tar.gz
epichains_0.1.1.9000.zip(r-4.7)epichains_0.1.1.9000.zip(r-4.6)epichains_0.1.1.9000.zip(r-4.5)
epichains_0.1.1.9000.tgz(r-4.6-any)epichains_0.1.1.9000.tgz(r-4.5-any)
epichains_0.1.1.9000.tar.gz(r-4.7-any)epichains_0.1.1.9000.tar.gz(r-4.6-any)
epichains_0.1.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
epichains/json (API)
NEWS
| # Install 'epichains' in R: |
| install.packages('epichains', repos = c('https://epiverse-trace.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/epiverse-trace/epichains/issues
Pkgdown/docs site:https://epiverse-trace.github.io
- covid19_sa - COVID-19 Data Repository for South Africa
branching-processesepidemic-dynamicsepidemic-modellingepidemic-simulationsepidemiologyepidemiology-modelsoutbreak-simulatortransmission-chaintransmission-chain-reconstruction
Last updated from:8ea4052884. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 129 | ||
| source / vignettes | OK | 226 | ||
| linux-release-x86_64 | OK | 123 | ||
| macos-release-arm64 | OK | 112 | ||
| macos-oldrel-arm64 | OK | 117 | ||
| windows-devel | OK | 77 | ||
| windows-release | OK | 72 | ||
| windows-oldrel | OK | 87 | ||
| wasm-release | OK | 106 |
Exports:dborellikelihoodrborelrgborelsimulate_chain_statssimulate_chains
Design Principles for {epichains}
Rendered fromdesign-principles.Rmdusingknitr::rmarkdownon May 09 2026.Last update: 2024-10-17
Started: 2024-05-15
Getting started with epichains
Rendered fromepichains.Rmdusingknitr::rmarkdownon May 09 2026.Last update: 2024-05-23
Started: 2023-09-02
Literature on branching process applications
Rendered frombranching_process_literature.Rmdusingknitr::rmarkdownon May 09 2026.Last update: 2024-06-21
Started: 2023-09-25
Modelling disease control interventions
Rendered frominterventions.Rmdusingknitr::rmarkdownon May 09 2026.Last update: 2024-10-17
Started: 2023-11-10
Projecting infectious disease incidence: a COVID-19 example
Rendered fromprojecting_incidence.Rmdusingknitr::rmarkdownon May 09 2026.Last update: 2024-10-17
Started: 2023-03-06
Theoretical background for epichains
Rendered fromtheoretical_background.Rmdusingknitr::rmarkdownon May 09 2026.Last update: 2025-08-29
Started: 2023-09-25
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Aggregate cases in <epichains> objects by "generation" or "time", if present | aggregate.epichains |
| COVID-19 Data Repository for South Africa | covid19_sa |
| Density of the Borel distribution | dborel |
| 'head' and 'tail' method for <epichains> class | head.epichains tail.epichains |
| Estimate the log-likelihood/likelihood for observed branching processes | likelihood |
| Print an <epichains> object | print.epichains |
| Print an <epichains_summary> object | print.epichains_summary |
| Generate random numbers from the Borel distribution | rborel |
| Generate random numbers from a Gamma-Borel mixture distribution | rgborel |
| Simulate a vector of transmission chains statistics (sizes/lengths) | simulate_chain_stats |
| Simulate transmission chains | simulate_chains |
| Summary method for <epichains> class | summary.epichains |
| Summary method for <epichains_summary> class | summary.epichains_summary |
