# Bayesian Methods for the Physical Science. Learning from
# Examples in Astronomy and Physics. By S. Andreon and B. Weaver.
model {
intrscat[1] ~ dunif(0,3)
intrscat[2] ~ dunif(0,3)
intrscat[3] ~ dunif(0,3)

alpha[1] ~ dnorm(0.0,1.0E-4)
alpha[2] ~ dnorm(0.0,1.0E-4)
alpha[3] ~ dnorm(0.0,1.0E-4)

beta ~ dt(0,1,1)
for (i in 1:length(x1)) {
 # modeling y
 obsy1[i] ~ dnorm(y1[i],pow(err.obsy1[i],-2))
 y1[i] ~ dnorm(z1[i],pow(intrscat[1],-2))	
 # modeling y-x
 z1[i] <- alpha[1]+0.1+beta*(x1[i]-0.03)
} 
for (i in 1:length(x2)) {
 # modeling y
 obsy2[i] ~ dnorm(y2[i],pow(err.obsy2[i],-2))
 y2[i] ~ dnorm(z2[i],pow(intrscat[2],-2))	
 # modeling y-x
 z2[i] <- alpha[2]+0.1+beta*(x2[i]-0.03)
} 
for (i in 1:length(x3)) {
 # modeling y
 obsy3[i] ~ dnorm(y3[i],pow(err.obsy3[i],-2))
 y3[i] ~ dnorm(z3[i],pow(intrscat[3],-2))	
 # modeling y-x
 z3[i] <- alpha[3]+0.1+beta*(x3[i]-0.03)
} 
}