SIRsim: Markovian SIR epidemic model

In dennisprangle/lazyABCexample: Implement "Lazy ABC" paper example

Description

Simulate from a Markovian SIR epidemic model.

Usage

SIRsim(beta, gamma, S0, I0, R0, t0, norm_beta = TRUE, t_end = Inf,
  step_end = Inf, thinning = 0)

Arguments

beta	The infection parameter
gamma	Recovery rate
S0	Initial number susceptible
I0	Initial number infectious
R0	Initial number recovered
t0	Initial time
norm_beta	Whether beta should be normalised (i.e. divided) by population size
t_end	Time at which the simulation will terminate
step_end	Number of steps after which the simulation will terminate
thinning	An integer determining what type of output to return. Zero gives the final state. A positive value thins the output by this factor i.e. output=1 gives all output, output=2 gives results for step 0,2,4,... The final state is always returned.

Details

This function performs a simulation. This terminates when (a) the specified time is reached or (b) the specified number of steps have been performed or (c) zero infectious remain. A simulation terminated for (a) or (b) can be continued by starting another simulation from the final state.

Value

A dataframe with columns step (number of steps performed), S, I, R (state at this step) and elapsed (computer time taken). The steps reported depend on the thinning variable.

dennisprangle/lazyABCexample documentation built on May 15, 2019, 3:25 a.m.