Define a recipe resulting in distributions from the same family
Conjugacy refers to when a prior
p(θ) and likelihood p(D|θ) pair yields a closed-form posterior p(θ|D). Formally, a prior p(θ) ∈ F is conjugate to likelihood p(D|θ) if the posterior belongs to the same parametric family p(θ|D) ∈ F, meaning F is closed under Bayesian updating.Conjugacy is the fact that a pair of prior and likelihood results in a closed form posterior, and we say that the prior is conjugate to the likelihood.