tau: Gillespie tau-leap algorithm

In epimdr: Functions and Data for "Epidemics: Models and Data in R"

Description

Function simulating a dynamical system using the Gillespie tau-leap approximation

Usage

tau(rateqs, eventmatrix, parameters, initialvals, deltaT, endT)

Arguments

rateqs	a list with rate equations
eventmatrix	a matrix of changes in state variables associated with each event
parameters	a vector of parameter values
initialvals	a vector of initial values for the states
deltaT	the tau-leap time interval
endT	the time length of simulation

Value

A data frame with simulated time series

Examples

rlist2=c(quote(mu * (S+E+I+R)), quote(mu * S), quote(beta * S * I/(S+E+I+R)), 
 quote(mu*E), quote(sigma * E), quote(mu * I), quote(gamma * I), quote(mu*R))
emat2=matrix(c(1,0,0,0,-1,0,0,0,-1,1,0,0,0,-1,0,0,0,-1,1,0,0,0,-1,0,0,0,-1,1,0,0,0,-1),
ncol=4, byrow=TRUE)
paras  = c(mu = 1, beta =  1000, sigma = 365/8, gamma = 365/5)
inits = c(S=999, E=0, I=1, R = 0)
sim2=tau(rlist2, emat2, paras, inits, 1/365, 1)

Example output

Loading required package: shiny
Loading required package: deSolve
Loading required package: polspline

epimdr documentation built on March 26, 2020, 7:41 p.m.