Priors

A key concept in Bayesian modeling. Priors represent existing, evidence-based beliefs about how a variable behaves before new data is analysed. They might come from past models, validated experiments, or industry benchmarks. Priors act as a stabilising influence when data is noisy, limited, or rapidly changing — ensuring early estimates remain realistic while still flexible enough to adapt as new signals appear.