As a full-blown Bayesian, I feel that the bayesian approach is almost perfect. It was a revelation when I first realized that instead of having this big frequentist toolbox of heuristics, one can simply assume that every involved entity is a random variable. Then everything is solved! But then pretty quickly I came to the catch, namely that to be able to do anything, the probability distributions must be parameterized. And then you start to wonder what the pdf's of the parameters should be, and off we go into infinite regress.
But the biggest catch is of course that the integral for the posterior is almost never solvable. If that wasn't the case,... (read more)
As a full-blown Bayesian, I feel that the bayesian approach is almost perfect. It was a revelation when I first realized that instead of having this big frequentist toolbox of heuristics, one can simply assume that every involved entity is a random variable. Then everything is solved! But then pretty quickly I came to the catch, namely that to be able to do anything, the probability distributions must be parameterized. And then you start to wonder what the pdf's of the parameters should be, and off we go into infinite regress.
But the biggest catch is of course that the integral for the posterior is almost never solvable. If that wasn't the case,... (read more)