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Bayesian Estimation Using a Non-Diffuse Prior Distribution
Is this solution proper? The posterior mean of each variance is positive, but a glance at
the Min column shows that some of the sampled values for the variance of e2 and the
variance of e3 are negative. To avoid negative variances for e2 and e3, we can modify
their prior distributions just as we did for e5.
It is not too difficult to impose such constraints on a parameter-by-parameter basis
in small models like this one. However, there is also a way to automatically set the
prior density to 0 for any parameter values that are improper. To use this feature: