Index: The Book of Statistical ProofsGeneral Theorems ▷ Frequentist statistics ▷ Likelihood theory ▷ Maximum log-likelihood

Definition: Let there be a generative model $m$ describing measured data $y$ using model parameters $\theta$. Then, the maximum log-likelihood (MLL) of $m$ is the maximal value of the log-likelihood function of this model:

\[\label{eq:mll} \mathrm{MLL}(m) = \operatorname*{max}_\theta \mathrm{LL}_m(\theta) \; .\]

The maximum log-likelihood can be obtained by plugging the maximum likelihood estimates into the log-likelihood function.


Metadata: ID: D61 | shortcut: mll | author: JoramSoch | date: 2020-05-15, 23:13.