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Higher-order asymptotics for the parametric complexity
The parametric complexity is the key quantity in the minimum description length (MDL) approach to statistical model selection.
Volumes of logistic regression models with applications to model selection
Logistic regression models with $n$ observations and $q$ linearly-independent covariates are shown to have Fisher information volumes which are bounded below by $\pi^q$ and above by ${n \choose q} \pi^q$.
SMML estimators for exponential families with continuous sufficient statistics
The minimum message length principle is an information theoretic criterion that links data compression with statistical inference.
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