Definition: Posterior model probability
Index: The Book of Statistical Proofs ▷ Model Selection ▷ Bayesian model selection ▷ Posterior model probability ▷ Definition
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Metadata: ID: D87 | shortcut: pmp | author: JoramSoch | date: 2020-07-28, 03:30.
Definition: Let $m_1, \ldots, m_M$ be $M$ statistical models with model evidences $p(y \vert m_1), \ldots, p(y \vert m_M)$ and prior probabilities $p(m_1), \ldots, p(m_M)$. Then, the conditional probability of model $m_i$, given the data $y$, is called the posterior probability of model $m_i$:
\[\label{eq:PMP} \mathrm{PP}(m_i) = p(m_i|y) \; .\]- Soch J, Allefeld C (2018): "MACS – a new SPM toolbox for model assessment, comparison and selection"; in: Journal of Neuroscience Methods, vol. 306, pp. 19-31, eq. 23; URL: https://www.sciencedirect.com/science/article/pii/S0165027018301468; DOI: 10.1016/j.jneumeth.2018.05.017.
Metadata: ID: D87 | shortcut: pmp | author: JoramSoch | date: 2020-07-28, 03:30.