# Mean square error for Bayesian estimate

I am trying to work on Bayesian linear regression. i have Classical and Bayesian regression estimates, now i want to find the Mean square error (MSE) for both approaches. Is the formula to find MSE will remain same i.e $MSE = \sum_i(y_i-\hat{y})^2/(n-k)$. k(parameters=2).

• I would rather estimate $\hat{y}$ in the model and then take averages of those estimates. – Tim Dec 17 '14 at 9:54