what's in a Bayesian fitting what is the problem with using a Bayesian model what is the function of the posterior in a Bayesian fit? explain. why are the posterior and the posterior of the model different and the convergence is bad which condition is used when p converges why does the posterior of p$ have to be the same what is the probability of a convergence of the posterior what makes a model converge which order of magnitude is used to find the posterior value why does the posterior value of p$ have an order of magnitude how to find the order of magnitude in a bayesian fitting what is the posterior of the bayesian model what is p in the Bayesian model what is the function of posterior what is the order of magnitude converges in a bayesian model how to find if the posterior is positive or negative when does the posterior equation converge why does $p take over the convergence why does p take over when converged why does p_pixelmetric$ take over the convergence