SIRstoch: Stochastic SIR dynamics

In CharlotteJana/pdmpsim: Simulate Piecewise Deterministic Markov Processes

Description

This is a more complicated example for a markov jump process defined as mjpModel. It is included to the package for demonstration purposes.

Usage

SIRstoch

Format

An object of class mjpModel.

Slots

parms

infection (beta) and recovery rate (gamma).

init

There are three integer variables S,I,R with initial value (10,1,0).

jumpfunc

There are two jumptypes. infections jump from (S,I,R) to (S-1,I+1,R), recoveries from (S,I,R) to (S,I-1,R+1).

ratefunc

A vector of length two determining the probability of a jump being a recovery or infection.

times

The simulations will start at time t = 0 and end at t = 10 with step length 0.01.

See Also

KendallBD for a simpler example of a mjpModel and mjpModel-class for the formal description of the S4 class.

Examples

## the code used to generate this model:

SIRstoch <- mjpModel(
    descr = "stochastic SIR epidemic",
    init = c(S=10,I=1,R=0),
    times = c(from = 0, to = 10, by = 0.01),
    ratefunc = function(t, x, parms) c(parms[1]*x[1]*x[2],parms[2]*x[2]),
    jumpfunc = function(t, x, parms, jtype){
         x+switch(jtype,c(-1,1,0),c(0,-1,1))
    },
    parms=c(beta=1,gamma=1))

## load it and plot a simulation:
data("SIRstoch")
plot(sim(SIRstoch))

CharlotteJana/pdmpsim documentation built on July 2, 2019, 5:37 a.m.