data(Epil)
my.center = function(x) (x - mean(x))

Epil$CTrt    = my.center(Epil$Trt)
Epil$ClBase4 = my.center(log(Epil$Base/4))
Epil$CV4     = my.center(Epil$V4)
Epil$ClAge   = my.center(log(Epil$Age))

formula = y ~ ClBase4*CTrt + ClAge + CV4 +
    f(Ind, model="iid") + f(rand, model="iid")

## Now I want the posterior for
##
##   1)    2*CTrt - CV4
##   2)    Ind[2] - rand[2]
##       
lc1 = inla.make.lincomb( CTrt = 2, CV4 = -1)
names(lc1) = "lc1"
lc2 = inla.make.lincomb( Ind = c(NA,1), rand = c(NA,-1))
names(lc2) = "lc2"

## default is to derive the marginals from lc's without changing the
## latent field
result1 = inla(formula,family="poisson", data = Epil,
        lincomb = c(lc1, lc2), verbose=TRUE, keep=TRUE,
        control.compute=list(q=TRUE))

## but the lincombs can also be additionally included into the latent
## field for increased accurancy...
result2 = inla(formula,family="poisson", data = Epil,
        lincomb = c(lc1, lc2), verbose=TRUE, keep=TRUE,
        control.inla = list(lincomb.derived.only = FALSE),
        control.compute = list(q=TRUE))