{ "_id": "6a1afcd71d7bb097a09fd7be", "Package": "SimInf", "Title": "A Framework for Data-Driven Stochastic Disease Spread\nSimulations", "Version": "10.1.0.9000", "Authors@R": "c(person(\"Stefan\", \"Widgren\", role = c(\"aut\", \"cre\"),\nemail = \"stefan.widgren@gmail.com\",\ncomment = c(ORCID = \"0000-0001-5745-2284\")),\nperson(\"Robin\", \"Eriksson\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-4291-712X\")),\nperson(\"Stefan\", \"Engblom\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-3614-1732\")),\nperson(\"Pavol\", \"Bauer\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-4328-7171\")),\nperson(\"Thomas\", \"Rosendal\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0002-6576-9668\")),\nperson(\"Ivana\", \"Rodriguez Ewerlöf\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0002-9678-9813\")),\nperson(\"Attractive Chaos\", role = \"cph\",\ncomment = \"Author of 'kvec.h'.\"))", "Description": "Provides an efficient and very flexible framework to\nconduct data-driven epidemiological modeling in realistic large\nscale disease spread simulations. The framework integrates\ninfection dynamics in subpopulations as continuous-time Markov\nchains using the Gillespie stochastic simulation algorithm and\nincorporates available data such as births, deaths and\nmovements as scheduled events at predefined time-points. Using\nC code for the numerical solvers and 'OpenMP' (if available) to\ndivide work over multiple processors ensures high performance\nwhen simulating a sample outcome. One of our design goals was\nto make the package extendable and enable usage of the\nnumerical solvers from other R extension packages in order to\nfacilitate complex epidemiological research. The package\ncontains template models and can be extended with user-defined\nmodels. For more details see the paper by Widgren, Bauer,\nEriksson and Engblom (2019) . The\npackage also provides functionality to fit models to time\nseries data using the Approximate Bayesian Computation\nSequential Monte Carlo ('ABC-SMC') algorithm of Toni and others\n(2009) or the Particle Markov\nChain Monte Carlo ('PMCMC') algorithm of 'Andrieu' and others\n(2010) .", "Acknowledgements": "This software has been made possible by support from\nthe Swedish Research Council within the UPMARC Linnaeus center\nof Excellence (Pavol Bauer, Robin Eriksson, and Stefan\nEngblom), the Swedish Research Council Formas (Stefan Engblom\nand Stefan Widgren), the Swedish Board of Agriculture (Stefan\nWidgren), the Swedish strategic research program eSSENCE\n(Stefan Widgren), and in the framework of the Full Force\nproject, supported by funding from the European Union’s Horizon\n2020 Research and Innovation programme under grant agreement No\n773830: One Health European Joint Programme (Stefan Widgren).", "License": "GPL-3", "URL": "https://github.com/stewid/SimInf, https://stewid.github.io/SimInf/", "BugReports": "https://github.com/stewid/SimInf/issues", "Type": "Package", "LazyData": "true", "Biarch": "true", "NeedsCompilation": "yes", "SystemRequirements": "GNU Scientific Library (GSL)", "Collate": "'C-generator.R' 'check_arguments.R' 'init.R' 'valid.R'\n'classes.R' 'SimInf_model.R' 'SEIR.R' 'SIR.R' 'SIS.R' 'SISe.R'\n'SISe3.R' 'SISe3_sp.R' 'SISe_sp.R' 'SimInf-package.R'\n'SimInf.R' 'SimInf_events.R' 'SimInf_individual_events.R'\n'run.R' 'density_ratio.R' 'abc.R' 'degree.R' 'distance.R'\n'distributions.R' 'edge_properties.R' 'lambert.R'\n'match_compartments.R' 'mparse.R' 'pmcmc.R' 'pfilter.R' 'n.R'\n'openmp.R' 'package_skeleton.R' 'plot.R' 'prevalence.R'\n'print.R' 'punchcard.R' 'trajectory.R' 'u0.R' 'v0.R'", "Encoding": "UTF-8", "VignetteBuilder": "utils, knitr", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "libgsl0-dev", "Repository": "https://stewid.r-universe.dev", "Date/Publication": "2026-05-30 07:41:09 UTC", "RemoteUrl": "https://github.com/stewid/siminf", "RemoteRef": "HEAD", "RemoteSha": "788bb3a28337ad76a55a3ff26b1a1c5f75ca0cda", "Packaged": { "Date": "2026-05-30 09:56:33 UTC", "User": "root" }, "Author": "Stefan Widgren [aut, cre] (ORCID:\n),\nRobin Eriksson [aut] (ORCID: ),\nStefan Engblom [aut] (ORCID: ),\nPavol Bauer [aut] (ORCID: ),\nThomas Rosendal [ctb] (ORCID: ),\nIvana Rodriguez Ewerlöf [ctb] (ORCID:\n),\nAttractive Chaos [cph] (Author of 'kvec.h'.)", "Maintainer": "Stefan Widgren ", "MD5sum": "80136c68232d3eedf407051dd032e890", "_user": "stewid", "_type": "src", "_file": "SimInf_10.1.0.9000.tar.gz", "_fileid": "973cee9fee01e8dc50f32a630126f27a294969752a248d2b27254cf730e3853e", "_filesize": 5191784, "_sha256": "973cee9fee01e8dc50f32a630126f27a294969752a248d2b27254cf730e3853e", "_created": "2026-05-30T09:56:33.000Z", "_published": "2026-05-30T15:05:59.003Z", "_distro": "noble", "_jobs": [ { "job": 78641097659, "time": 195, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", 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{ "page": "abc", "title": "Approximate Bayesian computation", "topics": [ "abc", "abc,SimInf_model-method" ] }, { "page": "add_spatial_coupling_to_ldata", "title": "Add spatial coupling information to local data", "topics": [ "add_spatial_coupling_to_ldata" ] }, { "page": "as.data.frame.SimInf_abc", "title": "Coerce a 'SimInf_abc' object to a 'data.frame'", "topics": [ "as.data.frame.SimInf_abc" ] }, { "page": "as.data.frame.SimInf_events", "title": "Coerce a 'SimInf_events' object to a 'data.frame'", "topics": [ "as.data.frame.SimInf_events" ] }, { "page": "as.data.frame.SimInf_individual_events", "title": "Coerce a 'SimInf_individual_events' object to a 'data.frame'", "topics": [ "as.data.frame.SimInf_individual_events" ] }, { "page": "as.data.frame.SimInf_pmcmc", "title": "Coerce a 'SimInf_pmcmc' object to a 'data.frame'", "topics": [ "as.data.frame.SimInf_pmcmc" ] }, { "page": "boxplot-SimInf_model-method", "title": "Box plot of number of individuals in each compartment", "topics": [ "boxplot,SimInf_model-method" ] }, { "page": "C_code", "title": "Extract the C code from a 'SimInf_model' object", "topics": [ "C_code" ] }, { "page": "continue_abc", "title": "Run more generations of ABC SMC", "topics": [ "continue_abc", "continue_abc,SimInf_abc-method" ] }, { "page": "continue_pmcmc", "title": "Continue PMCMC from an Existing Chain", "topics": [ "continue_pmcmc", "continue_pmcmc,SimInf_pmcmc-method" ] }, { "page": "distance_matrix", "title": "Create a distance matrix between nodes for spatial models", "topics": [ "distance_matrix" ] }, { "page": "edge_properties_to_matrix", "title": "Convert an edge list with properties to a matrix", "topics": [ "edge_properties_to_matrix" ] }, { "page": "events", "title": "Extract the scheduled events from a 'SimInf_model' object", "topics": [ "events", "events,SimInf_model-method" ] }, { "page": "events_SEIR", "title": "Example event data for the SEIR model with cattle herds", "topics": [ "events_SEIR" ] }, { "page": "events_SIR", "title": "Example event data for the SIR model with cattle herds", "topics": [ "events_SIR" ] }, { "page": "events_SIS", "title": "Example event data for the SIS model with cattle herds", "topics": [ "events_SIS" ] }, { "page": "events_SISe3", "title": "Example event data for the SISe3 model with cattle herds", "topics": [ "events_SISe3" ] }, { "page": "gdata", "title": "Extract global data from a 'SimInf_model' object", "topics": [ "gdata", "gdata,SimInf_model-method" ] }, { "page": "gdata-set", "title": "Set a global data parameter for a 'SimInf_model' object", "topics": [ "gdata<-", "gdata<-,SimInf_model-method" ] }, { "page": "get_individuals", "title": "Extract individuals from 'SimInf_individual_events'", "topics": [ "get_individuals", "get_individuals,SimInf_individual_events-method" ] }, { "page": "indegree", "title": "Determine in-degree for each node in a model", "topics": [ "indegree" ] }, { "page": "individual_events", "title": "Individual events", "topics": [ "individual_events" ] }, { "page": "lambertW0", "title": "Lambert W0 function", "topics": [ "lambertW0" ] }, { "page": "ldata", "title": "Extract local data from a node", "topics": [ "ldata", "ldata,SimInf_model-method" ] }, { "page": "length-SimInf_pmcmc-method", "title": "Length of the MCMC chain", "topics": [ "length,SimInf_pmcmc-method" ] }, { "page": "logLik-SimInf_pfilter-method", "title": "Log likelihood", "topics": [ "logLik,SimInf_pfilter-method" ] }, { "page": "mparse", "title": "Model parser to define new models for 'SimInf'", "topics": [ "mparse" ] }, { "page": "n_compartments", "title": "Determine the number of compartments in a model", "topics": [ "n_compartments", "n_compartments,SimInf_model-method" ] }, { "page": "n_generations", "title": "Determine the number of generations in an ABC analysis", "topics": [ "n_generations", "n_generations,SimInf_abc-method" ] }, { "page": "n_nodes", "title": "Determine the number of nodes in a model", "topics": [ "n_nodes", "n_nodes,SimInf_model-method", "n_nodes,SimInf_pfilter-method", "n_nodes,SimInf_pmcmc-method" ] }, { "page": "n_replicates", "title": "Determine the number of replicates in a model", "topics": [ "n_replicates", "n_replicates,SimInf_model-method" ] }, { "page": "node_events", "title": "Transform individual events to node events for a model", "topics": [ "node_events", "node_events,SimInf_individual_events-method" ] }, { "page": "nodes", "title": "Example data with spatial distribution of nodes", "topics": [ "nodes" ] }, { "page": "outdegree", "title": "Determine out-degree for each node in a model", "topics": [ "outdegree" ] }, { "page": "package_skeleton", "title": "Create a package skeleton from a 'SimInf_model'", "topics": [ "package_skeleton" ] }, { "page": "pairs-SimInf_model-method", "title": "Scatterplot matrix of number of individuals in each compartment", "topics": [ "pairs,SimInf_model-method" ] }, { "page": "pfilter", "title": "Bootstrap particle filter", "topics": [ 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"pmcmc", "pmcmc,SimInf_model-method" ] }, { "page": "prevalence", "title": "Generic function to calculate prevalence from trajectory data", "topics": [ "prevalence" ] }, { "page": "prevalence-SimInf_model-method", "title": "Calculate prevalence from a model object with trajectory data", "topics": [ "prevalence,SimInf_model-method" ] }, { "page": "prevalence-SimInf_pfilter-method", "title": "Extract prevalence from running a particle filter", "topics": [ "prevalence,SimInf_pfilter-method" ] }, { "page": "prevalence-SimInf_pmcmc-method", "title": "Extract prevalence from fitting a PMCMC algorithm", "topics": [ "prevalence,SimInf_pmcmc-method" ] }, { "page": "punchcard-set", "title": "Set a sparse recording template for simulation results", "topics": [ "punchcard<-", "punchcard<-,SimInf_model-method" ] }, { "page": "run", "title": "Run the SimInf stochastic simulation algorithm", "topics": [ "run", "run,SEIR-method", "run,SimInf_abc-method", "run,SimInf_model-method", "run,SIR-method", "run,SIS-method", "run,SISe-method", "run,SISe3-method", "run,SISe3_sp-method", "run,SISe_sp-method" ] }, { "page": "SEIR", "title": "Create an SEIR model", "topics": [ "SEIR" ] }, { "page": "SEIR-class", "title": "Class SEIR", "topics": [ "SEIR-class" ] }, { "page": "select_matrix", "title": "Extract the select matrix from a 'SimInf_model' object", "topics": [ "select_matrix", "select_matrix,SimInf_model-method" ] }, { "page": "select_matrix-set", "title": "Set the select matrix for a 'SimInf_model' object", "topics": [ "select_matrix<-", "select_matrix<-,SimInf_model-method" ] }, { "page": "set_num_threads", "title": "Specify the number of threads that SimInf should use", "topics": [ "set_num_threads" ] }, { "page": "shift_matrix", "title": "Extract the shift matrix from a 'SimInf_model' object", "topics": [ "shift_matrix", "shift_matrix,SimInf_model-method" ] }, { "page": "shift_matrix-set", "title": "Set the shift matrix for a 'SimInf_model' object", "topics": [ "shift_matrix<-", "shift_matrix<-,SimInf_model-method" ] }, { "page": "show-SimInf_abc-method", "title": "Print summary of a 'SimInf_abc' object", "topics": [ "show,SimInf_abc-method" ] }, { "page": "show-SimInf_events-method", "title": "Brief summary of 'SimInf_events'", "topics": [ "show,SimInf_events-method" ] }, { "page": "show-SimInf_individual_events-method", "title": "Print summary of a 'SimInf_individual_events' object", "topics": [ "show,SimInf_individual_events-method" ] }, { "page": "show-SimInf_model-method", "title": "Brief summary of 'SimInf_model'", "topics": [ "show,SimInf_model-method" ] }, { "page": "show-SimInf_pfilter-method", "title": "Brief summary of a 'SimInf_pfilter' object", "topics": [ "show,SimInf_pfilter-method" ] }, { "page": "show-SimInf_pmcmc-method", "title": "Brief summary of a 'SimInf_pmcmc' object", "topics": [ "show,SimInf_pmcmc-method" ] }, { "page": "SimInf", "title": "A Framework for Data-Driven Stochastic Disease Spread Simulations", "topics": [ "SimInf-package", "SimInf" ] }, { "page": "SimInf_abc-class", "title": "Class 'SimInf_abc'", "topics": [ "SimInf_abc-class" ] }, { "page": "SimInf_events", "title": "Create a 'SimInf_events' object", "topics": [ "SimInf_events" ] }, { "page": "SimInf_events-class", "title": "Class 'SimInf_events'", "topics": [ "SimInf_events-class" ] }, { "page": "SimInf_individual_events-class", "title": "Class 'SimInf_individual_events'", "topics": [ "SimInf_individual_events-class" ] }, { "page": "SimInf_model", "title": "Create a 'SimInf_model' object", "topics": [ "SimInf_model" ] }, { "page": "SimInf_model-class", "title": "Class 'SimInf_model'", "topics": [ "SimInf_model-class" ] }, { "page": "SimInf_pfilter-class", "title": "Class '\"SimInf_pfilter\"'", "topics": [ "SimInf_pfilter-class" ] }, { "page": "SimInf_pmcmc-class", "title": "Class 'SimInf_pmcmc'", "topics": [ "SimInf_pmcmc-class" ] }, { "page": "SIR", "title": "Create an SIR model", "topics": [ "SIR" ] }, { "page": "SIR-class", "title": "Class SIR", "topics": [ "SIR-class" ] }, { "page": "SIS", "title": "Create an SIS model", "topics": [ "SIS" ] }, { "page": "SIS-class", "title": "Class SIS", "topics": [ "SIS-class" ] }, { "page": "SISe", "title": "Create an SISe model", "topics": [ "SISe" ] }, { "page": "SISe_sp", "title": "Create an SISe_sp model", "topics": [ "SISe_sp" ] }, { "page": "SISe_sp-class", "title": "Class SISe_sp", "topics": [ "SISe_sp-class" ] }, { "page": "SISe-class", "title": "Class SISe", "topics": [ "SISe-class" ] }, { "page": "SISe3", "title": "Create a 'SISe3' model", "topics": [ "SISe3" ] }, { "page": "SISe3_sp", "title": "Create an SISe3_sp model", "topics": [ "SISe3_sp" ] }, { "page": "SISe3_sp-class", "title": "Class SISe3_sp", "topics": [ "SISe3_sp-class" ] }, { "page": "SISe3-class", "title": "Class SISe3", "topics": [ "SISe3-class" ] }, { "page": "summary-SimInf_abc-method", "title": "Detailed summary of a 'SimInf_abc' object", "topics": [ "summary,SimInf_abc-method" ] }, { "page": 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