Line: Linear Regression
model
{
for( i in 1 : N ) {
Y[i] ~ dnorm(mu[i],tau)
mu[i] <- alpha + beta * (x[i] - xbar)
}
tau ~ dgamma(0.001,0.001) sigma <- 1 / sqrt(tau)
alpha ~ dnorm(0.0,1.0E-6)
beta ~ dnorm(0.0,1.0E-6)
}
Data
( click to open )
Inits
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Results
A 1000 update burn in followed by a further 10000 updates gave the parameter estimates