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{title2=$D(\theta_1,\theta_2)$}

= Deviance
{synonym}

The deviance from $\theta_1$ to $\theta_2$ is twice the <Kullback-Leibler divergence>:
$$
D(\theta_1,\theta_2)
=2\mathbb E_{\theta_1}\!\left[
\log\frac{f_{\theta_1}(Y)}{f_{\theta_2}(Y)}
\right].
$$

Exponential-family deviance

Bayesian deviance

Past exam of the mathematics course of the University of Cambridge / 2022 / iii / Paper 218 / 1 / d / Solution

Past exam of the mathematics course of the University of Cambridge / 2023 / ii / Paper 3 / 5J / Solution

codex/deviance

Exponential-family deviance ( $D (θ_{1}, θ_{2})$ )

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Exponential-family deviance (D(θ1​,θ2​))