Do we dispose of some type of guarantee that these priors imitate the shape of the likelihood in such a way that the posterior distribution delivers us a result close enough to the Maximum Likelihood Estimate?
Hi folks.
I've a question.
Let k be a parameter which must be estimated. It lies within the interval (a;b), a and b being finite real numbers.
Let us further assume we dispose of a series of measurements X of known standard deviations.
X is a complex function of k.
What are Jeffreys...