A Framework for Data-Driven Stochastic Disease Spread Simulations


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Documentation for package ‘SimInf’ version 11.1.0

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A B C D E G I L M N O P R S T U V

SimInf-package A Framework for Data-Driven Stochastic Disease Spread Simulations

-- A --

abc Approximate Bayesian computation
abc-method Approximate Bayesian computation
add_spatial_coupling_to_ldata Add spatial coupling information to local data
as.data.frame.SimInf_abc Coerce a 'SimInf_abc' object to a 'data.frame'
as.data.frame.SimInf_events Coerce a 'SimInf_events' object to a 'data.frame'
as.data.frame.SimInf_individual_events Coerce a 'SimInf_individual_events' object to a 'data.frame'
as.data.frame.SimInf_pmcmc Coerce a 'SimInf_pmcmc' object to a 'data.frame'

-- B --

boxplot-method Box plot of number of individuals in each compartment

-- C --

continue_abc Run more generations of ABC SMC
continue_abc-method Run more generations of ABC SMC
continue_pmcmc Continue PMCMC from an Existing Chain
continue_pmcmc-method Continue PMCMC from an Existing Chain
C_code Extract the C code from a 'SimInf_model' object

-- D --

distance_matrix Create a distance matrix between nodes for spatial models

-- E --

edge_properties_to_matrix Convert an edge list with properties to a matrix
events Extract the scheduled events from a 'SimInf_model' object
events-method Extract the scheduled events from a 'SimInf_model' object
events_SEIR Example event data for the SEIR model with cattle herds
events_SIR Example event data for the SIR model with cattle herds
events_SIS Example event data for the SIS model with cattle herds
events_SISe3 Example event data for the SISe3 model with cattle herds

-- G --

gdata Extract global data from a 'SimInf_model' object
gdata-method Extract global data from a 'SimInf_model' object
gdata<- Set a global data parameter for a 'SimInf_model' object
gdata<--method Set a global data parameter for a 'SimInf_model' object
get_individuals Extract individuals from 'SimInf_individual_events'
get_individuals-method Extract individuals from 'SimInf_individual_events'

-- I --

indegree Determine in-degree for each node in a model
individual_events Individual events

-- L --

lambertW0 Lambert W0 function
ldata Extract local data from a node
ldata-method Extract local data from a node
length-method Length of the MCMC chain
logLik-method Extract Log-Likelihood

-- M --

mparse Model parser to define new models for 'SimInf'

-- N --

nodes Example data with spatial distribution of nodes
node_events Transform individual events to node events for a model
node_events-method Transform individual events to node events for a model
n_compartments Determine the number of compartments in a model
n_compartments-method Determine the number of compartments in a model
n_generations Determine the number of generations in an ABC analysis
n_generations-method Determine the number of generations in an ABC analysis
n_nodes Determine the number of nodes in a model
n_nodes-method Determine the number of nodes in a model
n_replicates Determine the number of replicates in a model
n_replicates-method Determine the number of replicates in a model

-- O --

outdegree Determine out-degree for each node in a model

-- P --

package_skeleton Create a package skeleton from a 'SimInf_model'
pairs-method Scatterplot matrix of number of individuals in each compartment
pfilter Bootstrap particle filter
pfilter-method Bootstrap particle filter
plot-method Display the ABC posterior distribution
plot-method Display the distribution of scheduled events over time
plot-method Display the distribution of individual events over time
plot-method Diagnostic plot of a particle filter object
plot-method Display the PMCMC posterior distribution
plot-method Display the outcome from a simulated trajectory
pmcmc Particle Markov chain Monte Carlo (PMCMC) algorithm
pmcmc-method Particle Markov chain Monte Carlo (PMCMC) algorithm
prevalence Generic function to calculate prevalence from trajectory data
prevalence-method Calculate prevalence from a model object with trajectory data
prevalence-method Extract prevalence from running a particle filter
prevalence-method Extract prevalence from fitting a PMCMC algorithm
punchcard<- Set a sparse recording template for simulation results
punchcard<--method Set a sparse recording template for simulation results

-- R --

run Run a SimInf model simulation
run-method Run a SimInf model simulation

-- S --

SEIR Create an SEIR model
SEIR-class Class SEIR
select_matrix Extract the select matrix from a 'SimInf_model' object
select_matrix-method Extract the select matrix from a 'SimInf_model' object
select_matrix<- Set the select matrix for a 'SimInf_model' object
select_matrix<--method Set the select matrix for a 'SimInf_model' object
set_num_threads Specify the number of threads that SimInf should use
shift_matrix Extract the shift matrix from a 'SimInf_model' object
shift_matrix-method Extract the shift matrix from a 'SimInf_model' object
shift_matrix<- Set the shift matrix for a 'SimInf_model' object
shift_matrix<--method Set the shift matrix for a 'SimInf_model' object
show-method Brief summary of a 'SimInf_abc' object
show-method Brief summary of a 'SimInf_events' object
show-method Brief summary of a 'SimInf_individual_events' object
show-method Brief summary of a 'SimInf_model' object
show-method Brief summary of a 'SimInf_pfilter' object
show-method Brief summary of a 'SimInf_pmcmc' object
SimInf A Framework for Data-Driven Stochastic Disease Spread Simulations
SimInf_abc-class Class 'SimInf_abc'
SimInf_events Create a 'SimInf_events' object
SimInf_events-class Class 'SimInf_events'
SimInf_individual_events-class Class 'SimInf_individual_events'
SimInf_model Create a 'SimInf_model' object
SimInf_model-class Class 'SimInf_model'
SimInf_pfilter-class Class 'SimInf_pfilter'
SimInf_pmcmc-class Class 'SimInf_pmcmc'
SIR Create an SIR model
SIR-class Class SIR
SIS Create an SIS model
SIS-class Class SIS
SISe Create an SISe model
SISe-class Class SISe
SISe3 Create a 'SISe3' model
SISe3-class Class SISe3
SISe3_sp Create an SISe3_sp model
SISe3_sp-class Class SISe3_sp
SISe_sp Create an SISe_sp model
SISe_sp-class Class SISe_sp
summary-method Detailed summary of a 'SimInf_abc' object
summary-method Detailed summary of a 'SimInf_events' object
summary-method Detailed summary of a 'SimInf_individual_events' object
summary-method Detailed summary of a 'SimInf_model' object
summary-method Detailed summary of a 'SimInf_pfilter' object
summary-method Detailed summary of a 'SimInf_pmcmc' object

-- T --

trajectory Generic function to extract data from a simulated trajectory
trajectory-method Extract data from a simulated trajectory
trajectory-method Extract filtered trajectory from running a particle filter

-- U --

u0 Get the initial compartment state ('u0') in each node
u0-method Get the initial compartment state ('u0') in each node
u0<- Update the initial compartment state ('u0') in each node
u0<--method Update the initial compartment state ('u0') in each node
u0_from_individual_events Derive the initial compartment state from individual events
u0_from_individual_events-method Derive the initial compartment state from individual events
u0_SEIR Example initial population data for the SEIR model
u0_SIR Example initial population data for the SIR model
u0_SIS Example initial population data for the SIS model
u0_SISe3 Example initial population data for the SISe3 model

-- V --

v0<- Update the initial continuous state ('v0') in each node
v0<--method Update the initial continuous state ('v0') in each node