##############################################
# Section 7.4 Mortality data (assuming common
mortality)
##############################################
model
{
for(i in 1:n)
{
y[i] ~ dpois(e.lambda[i]) #
likelihood
e.lambda[i]
<- e[i]*lambda
}
lambda ~ dgamma(0.001, 0.001) # prior
#
Posterior predictive analysis
#
Is one of E(pright[i]) and E(pleft[i]) less than 0.05?
#
If yes, the model may not be valid to describe i-th observation.
for(i in 1:n)
{
ypred[i] ~ dpois(e.lambda[i])
pright[i] <- step(ypred[i] - y[i])
pleft[i] <-
step(y[i] - ypred[i])
}
}
# Initial values. Initialize other values using "gen inits".
list( lambda = 1 )
# Data
list(n=94)
# Data
e[]
y[]
532 0
584 0
672 2
722 1
904 1
1236 0
950 0
1405 1
776 3
1013 0
739 0
1770 1
821 0
1115 2
1164 3
1164 0
1303 0
1774 3
3585 1
1193 1
1213 1
1232 1
1517 4
1520 3
1862 3
1888 1
1247 0
1381 2
1643 2
1660 4
1827 4
1486 3
1593 2
2265 4
1524 1
1759 3
1309 0
1529 4
1677 1
1654 2
1785 3
1979 4
1767 4
2465 2
1750 2
2458 4
2383 2
2717 3
2282 0
2115 0
2852 2
2856 5
3174 5
2369 1
2557 1
3859 3
2641 1
2741 1
3055 3
3513 1
2728 2
3354 6
3814 0
4014 2
2612 2
2815 1
4294 2
3450 8
3628 6
4219 1
3932 6
4082 4
4203 1
4022 3
4636 5
5571 2
6436 4
5344 3
4445 4
4705 5
5039 2
6043 6
5121 8
11260 5
5789 0
6044 6
5569 8
6130 7
6249 3
7002 3
7851 9
9573 7
12050 18
12131 17
END