Nothing
\donttest{
set.seed(123)
# Exponentially distributed transmission kernel with mean and standard deviation = 100
dist.func <- alist(n=1, a=1/100, rexp(n, a))
# Simulate epidemic
a <- sim.epidemic(R=2,
gen.t.mean=7,
gen.t.sd=2,
tot.generations=7,
min.cases=30,
trans.kern.func=dist.func)
a <- a[sample(1:nrow(a), 50),] # subsample a to 50 observations
# Estimate mean transmission kernel over time
b <- est.transdist.temporal(epi.data=a,
gen.t.mean=7,
gen.t.sd=2,
t1=0,
max.sep=1e10,
max.dist=1e10,
n.transtree.reps=5,
mean.equals.sd=TRUE,
n.cores=2)
b
plot(b[,2], pch=19, col='grey', ylim=c(min(b[,2], na.rm=TRUE), max(b[,2], na.rm=TRUE)),
xlab='Time step', ylab='Estimated mean of transmission kernel')
abline(h=100, col='red', lty=2)
axis(3, b[,2])
low <- loess(b[,2] ~ as.vector(1:length(b[,2])))
low <- predict(low, newdata=data.frame(as.vector(1:length(b[,2]))))
lines(low, lwd=3, col='blue')
}
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