Package: SIRmcmc 1.1.1
F Scott Dahlgren
SIRmcmc: Compartmental Susceptible-Infectious-Recovered (SIR) Model of Community and Household Infection
We build an Susceptible-Infectious-Recovered (SIR) model where the rate of infection is the sum of the household rate and the community rate. We estimate the posterior distribution of the parameters using the Metropolis algorithm. Further details may be found in: F Scott Dahlgren, Ivo M Foppa, Melissa S Stockwell, Celibell Y Vargas, Philip LaRussa, Carrie Reed (2021) "Household transmission of influenza A and B within a prospective cohort during the 2013-2014 and 2014-2015 seasons" <doi:10.1002/sim.9181>.
Authors:
SIRmcmc_1.1.1.tar.gz
SIRmcmc_1.1.1.tar.gz(r-4.5-noble)SIRmcmc_1.1.1.tar.gz(r-4.4-noble)
SIRmcmc_1.1.1.tgz(r-4.4-emscripten)SIRmcmc_1.1.1.tgz(r-4.3-emscripten)
SIRmcmc.pdf |SIRmcmc.html✨
SIRmcmc/json (API)
| # Install 'SIRmcmc' in R: |
| install.packages('SIRmcmc', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- hh.transmission - Simulated data under the SIR.
- hh.transmission.epsilon - Simulated data under SIR, with covariates.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 months agofrom:3b5bc0a419. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 08 2024 |
| R-4.5-linux-x86_64 | OK | Sep 08 2024 |
Exports:community_attack_ratehousehold_transmissionMCMC_datepriorsecondary_attack_rateunifprior
Dependencies:Rcpp
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute the community attack rate | community_attack_rate |
| Simulated data under the SIR. | hh.transmission |
| Simulated data under SIR, with covariates. | hh.transmission.epsilon |
| Estimate parameters from SIR model | household_transmission |
| Convert dates to a list of extendend natural numbers. | MCMC_date |
| Compute prior probability of parameters | prior |
| Compute the secondary attack rate | secondary_attack_rate |
| A uniform prior on the model parameters | unifprior |