model {
for (i in 1:A) { # 1:age 0-10 2:age 10-19
n.pos[i] ~ dbinom(p.pos, N[i])
n.sym[i] ~ dbinom(q[i], n.pos[i]) # q[i] : Pr[symptomatic|PCR+]
n.asy[i] <- n.pos[i] - n.sym[i]
Y.sym[i] ~ dbinom(p.obs.sym, n.sym[i])
Y.asy[i] ~ dbinom(p.obs.asy, n.asy[i])
Y.sym.DP[i] ~ dbinom(q[i], N.pos.DP[i])
logit(q[i]) <- q.x[i]
# q[i] <- ilogit(q.x[i])
}
n.pos.sum <- sum(n.pos)
p.pos ~ dbeta(0.5,0.5) # original : dbeta(0.5, 1)
p.obs.sym ~ dbeta(4, 2) # mean 0.667 sd 0.1781742
p.obs.asy ~ dbeta(2, 4) # mean 0.333 sd 0.1781742
q.x[1] ~ dnorm(0, 1e-4) # N(m=0,sd=100)
q.x[2] ~ dnorm(0, 1e-4)
for (j in 3:A) {
q.x[j] ~ dnorm(2*q.x[j-1] - q.x[j-2], tau)
}
tau ~ dt(0,pow(2.5,-2),1)T(0,)
# original : tau = pow(sigma,-2) ; sigma ~ dunif(0,5)
}