#JAGS model for Bayesian analysis of averages with informed priors 
# Pedro 05/25/2015

model {

  ## Priors
  mean_height~dnorm(m,v)        #informative prior for the mean height of the plants
  var_height~dlnorm(mv,vv)      #informative prior for the variance of the height of the plants
  prec <- 1/var_height          #precision = 1 / variance

  ## Likelihood
  for (i in 1:nobs){            #for each plant
  Y[i]~dnorm(mean_height,prec)  #assume the height comes from this normal distribution
  }

}