Roughly speaking, we can divide Bayesianism into two, maybe three or more, separate but related meanings:
1. Adherence to a form of Bayesian epistemology. You think that knowledge comes in degrees of belief, and the correct way to update your beliefs on seeing new information is to use Bayes theorem. It's usually done informally.
2. Adherence to Bayesian statistics. You believe that frequentist inference is invalid and that frequentist measures of an estimator's quality should not be used. Instead, you prefer to use precisely defined priors and likelihoods, ... (read more)
I haven't observed any rationalists here using Dirichlet, and no, I wasn't talking about Bayesian vs. Frequentist; Bayesians are correct. Using Bayes Theorem when you didn't consider the probability of each possibly population producing your observed sample? That's definitely you doing it wrong. Instrumentation has variability; Dirichlet is how you include that, too.
Roughly speaking, we can divide Bayesianism into two, maybe three or more, separate but related meanings:
1. Adherence to a form of Bayesian epistemology. You think that knowledge comes in degrees of belief, and the correct way to update your beliefs on seeing new information is to use Bayes theorem. It's usually done informally.
2. Adherence to Bayesian statistics. You believe that frequentist inference is invalid and that frequentist measures of an estimator's quality should not be used. Instead, you prefer to use precisely defined priors and likelihoods, ... (read more)