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SimInf (version 5.0.0)

A Framework for Data-Driven Stochastic Disease Spread Simulations

Description

Livestock movements are important for the spread of many infectious diseases between herds. The package provides an efficient and flexible framework for stochastic disease spread modelling that integrates within-herd disease dynamics as continuous-time Markov chains and livestock movements between herds as scheduled events. The core simulation solver is implemented in C and uses 'OpenMP' (if available) to divide work over multiple processors. The package contains template models and can be extended with user defined models.

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Version

Install

install.packages('SimInf')

Monthly Downloads

490

Version

5.0.0

License

GPL-3

Issues

1

Pull Requests

0

Stars

35

Forks

14

Maintainer

Stefan Widgren

Last Published

June 13th, 2017

Functions in SimInf (5.0.0)

SISe3

Create a SISe3 model
SISe3_sp-class

Class "SISe3_sp"
C_code

Extract the C code from an mparse object
SEIR-class

Class "SEIR"
SEIR

Create a SEIR model
SIR-class

Class "SIR"
SISe

Create a SISe model
SISe3-class

Class "SISe3"
SIR

Create a SIR model
SISe-class

Class "SISe"
SISe_sp

Create a SISe_sp model
SimInf

A Framework for Stochastic Disease Spread Simulations
check_end_t_arg

Check arguments for interval endpoints
SimInf_model-class

Class "SimInf_model"
SimInf_model

Create a SimInf_model
events_SISe

Scheduled events example data for the SISe model
SISe3_sp

Create a SISe3_sp model
SISe_sp-class

Class "SISe_sp"
check_infectious_pressure_arg

Check integer arguments
check_integer_arg

Check integer arguments
SimInf_mparse-class

Class "SimInf_mparse"
U

Extract the number of individuals in each compartment
V<-

Set a template for where to write the V result matrix
boxplot-methods

Box Plots
events_SISe3

Scheduled events example data
prevalence

Prevalence
recovered

Recovered
u0_SISe3

Example data to initialize a model
SimInf_events-class

Class "SimInf_events"
SimInf_events

Create a "'>SimInf_events" object
U<-

Set a template for where to write the U result matrix
V

Extract the continuous state variables
init

Init a SimInf_mparse object with data
is_wholenumber

Check if wholenumbers
plot-methods

Plot '>SimInf_events
events_SEIR

Scheduled events example data for the SEIR model
events_SIR

Scheduled events example data for the SIR model
package_skeleton

Describe your model in a logical way in R. mparse creates a '>SimInf_mparse object with your model definition that is ready to be initialised with data and then run. Create a package skeleton for a model depending on SimInf
pairs-methods

Scatterplot Matrices
mparse

Model parser
nodes

Example data with spatial distribution of nodes
show,SimInf_events-method

Brief summary of SimInf_events
show,SimInf_model-method

Brief summary of SimInf_model
distance_matrix

Create distance matrix
events

Extract the events from a SimInf_model object
have_openmp

Is OpenMP available
plot_SimInf_events

Plot scheduled events
summary,SimInf_events-method

Summary of SimInf_events
summary,SimInf_model-method

Summary of SimInf_model
check_gdata_arg

Check arguments for 'gdata'
susceptible

Susceptible
u0_SEIR

Example data to initialize the SEIR model
infected

Infected
u0_SIR

Example data to initialize the SIR model
u0_SISe

Example data to initialize the SISe model
run

Run the SimInf stochastic simulation algorithm
run_outer

Run SimInf_model on scaled parameters