model{

##################
# heritabilities #
##################

# use the greenhouse data as half-sibling families to get variance components
# data: n_greenhouse, n_moms, off, id
for(i in 1:n_greenhouse){
	off[i] ~ dnorm(mu_mom[id[i]], tau_within)
}

for(i in 1:n_moms){
	mu_mom[i] ~ dnorm(grand_mu, tau_among)
}

# priors
grand_mu ~ dnorm(0.0, 1.0)
var_within ~ dgamma(2.0, 2.0)
var_among ~ dgamma(2.0, 2.0)
var_total <- var_among + var_within
tau_within <- 1.0/var_within
tau_among <- 1.0/var_among

v_a <- ???
v_e <- ???
v_p <- ???
h_2 <- ??? 

###############################
# selection differential code #
###############################

# data: y = fitness of individual i
# 		x = field trait of individual i
#		n_field = number of individuals in field

for(i in 1:n_field){

	y[i] ~ dnorm(mu[i], tau)
	mu[i] <- beta.0 + beta.1*x[i]
}

# priors
beta.0 ~ dnorm(0.0, 1.0)
beta.1 ~ dnorm(0.0, 1.0)
var.resid ~ dgamma(2.0, 2.0)
tau <- 1.0/var.resid

S <- ???
R <- ???
}