Posterior Distribution
In Bayesian inference, the probability distribution over a parameter after combining the prior with observed data via Bayes' theorem.
Last updated: 2026-05-04
Definition
The posterior IS the answer in Bayesian MMM — every per-channel ROAS, adstock half-life, and saturation curvature lives inside its posterior distribution. Decision tools sit on top: the expected value (mean) feeds the budget optimizer; the credible interval feeds the dashboard; the full posterior feeds Thompson Sampling for exploration vs. exploitation.
How it applies in India
No India-specific behavior.
Related terms
- Bayesian MMMMarketing Mix Modeling implemented with Bayesian inference (typically MCMC sampling), producing posterior distributions over channel contributions instead of point estimates.
- Prior DistributionIn Bayesian inference, the probability distribution that encodes belief about a parameter before observing the data.
- Credible IntervalA range that contains the true parameter value with a stated probability (e.g., 95%). The Bayesian counterpart to a frequentist confidence interval.
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