Package: SimInf 9.8.1
SimInf: A Framework for Data-Driven Stochastic Disease Spread Simulations
Provides an efficient and very flexible framework to conduct data-driven epidemiological modeling in realistic large scale disease spread simulations. The framework integrates infection dynamics in subpopulations as continuous-time Markov chains using the Gillespie stochastic simulation algorithm and incorporates available data such as births, deaths and movements as scheduled events at predefined time-points. Using C code for the numerical solvers and 'OpenMP' (if available) to divide work over multiple processors ensures high performance when simulating a sample outcome. One of our design goals was to make the package extendable and enable usage of the numerical solvers from other R extension packages in order to facilitate complex epidemiological research. The package contains template models and can be extended with user-defined models. For more details see the paper by Widgren, Bauer, Eriksson and Engblom (2019) <doi:10.18637/jss.v091.i12>. The package also provides functionality to fit models to time series data using the Approximate Bayesian Computation Sequential Monte Carlo ('ABC-SMC') algorithm of Toni and others (2009) <doi:10.1098/rsif.2008.0172>.
Authors:
SimInf_9.8.1.tar.gz
SimInf_9.8.1.tar.gz(r-4.5-noble)SimInf_9.8.1.tar.gz(r-4.4-noble)
SimInf_9.8.1.tgz(r-4.4-emscripten)SimInf_9.8.1.tgz(r-4.3-emscripten)
SimInf.pdf |SimInf.html✨
SimInf/json (API)
NEWS
# Install 'SimInf' in R: |
install.packages('SimInf', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/stewid/siminf/issues
- events_SISe3 - Example data to initialize events for the 'SISe3' model
- nodes - Example data with spatial distribution of nodes
- u0_SISe3 - Example data to initialize the 'SISe3' model
Last updated 6 months agofrom:94b2d7b70c. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 21 2024 |
R-4.5-linux-x86_64 | OK | Nov 21 2024 |
Exports:abcboxplotC_codecontinuedistance_matrixedge_properties_to_matrixeventsevents_SEIRevents_SIRevents_SISevents_SISegdatagdata<-get_individualsindegreeindividual_eventsldatalogLikmparsen_generationsn_nodesnode_eventsoutdegreepackage_skeletonpairspfilterplotprevalencepunchcard<-runSEIRselect_matrixselect_matrix<-set_num_threadsshift_matrixshift_matrix<-showSimInf_eventsSimInf_modelSIRSISSISeSISe_spSISe3SISe3_spsummarytrajectoryu0u0_SEIRu0_SIRu0_SISu0_SISeu0<-v0<-
Post-process data in a trajectory
Rendered frompost-process-data.Rmd
usingknitr::rmarkdown
on Nov 21 2024.Last update: 2024-04-24
Started: 2024-04-24
Scheduled events
Rendered fromscheduled-events.Rmd
usingknitr::rmarkdown
on Nov 21 2024.Last update: 2024-04-24
Started: 2021-06-25
SimInf: An R Package for Data-Driven Stochastic Disease Spread Simulations
Rendered fromSimInf.Rnw
usingutils::Sweave
on Nov 21 2024.Last update: 2022-09-03
Started: 2017-06-13