SIR.MLE {stochasticGEM} | R Documentation |
SIR.MLE
is used to fit the standard SIR general epidemic model. This is an internal
function which can also be called directly by the user. It requires that the
epidemic is fully observed, implying that the infection times are also available.
SIR.MLE(parameters, N, infectionTimes, removalTimes, infectious.density = "exponential")
parameters |
starting values for parameters. a vector of length 2. needed by optim . |
N |
initial susceptible individuals |
infectionTimes |
infection times |
removalTimes |
removal times |
infectious.density |
type of density. can be either exponential , gamma and weibull |
a list
of components returned by optim
.
Eugene Zwane e.zwane@gmail.com
O'Neill, P.D. & Roberts, G.O. (1999). 'Bayesian inference for partially observed stochastic epidemics' J.R. Statist. Soc. A. 162, 121-129.
O'Neill, P.D. & Becker, N.G. (2001). 'Inference for an epidemic when susceptibility varies' Biostatistics 2, 99-108.
Streftaris, G. & Gibson, G.J. (2004). 'Bayesian inference for stochastic epidemics in closed populations' Statistical Modelling 4, 63-75.
data(smallpox) SIR.MLE(c(1/1000,1/10), 119, smallpox-16, smallpox, infectious.density = "exponential")