Notation of parts of Bayes’s Theorem

The symbol P to denote probability is a bit overloaded. To help aid in notation, we will use the following conventions going forward in the class.

  • Probability densities describing measured data are denoted with f.

  • Probability densities describing parameter values, hypotheses, or other non-measured quantities, are denoted with g.

  • A set of parameters for a given model are denoted θ.

So, if we were to write down Bayes’s theorem for a parameter estimation problem, it would be

g(θy)=f(yθ)g(θ)f(y).

Probabilities written with a g denote the prior or posterior, and those with an f denote the likelihood or evidence.