4 papers
Entropic Strict Minimum Message Length and Its Connections to PAC-Bayes and NML
Enes Makalic, Daniel F. Schmidt
We introduce entropic strict minimum message length (SMML), a risk-sensitive generalization of strict minimum message length coding. The proposed criterion replaces expected two-pa…
Asymptotic theory and first-order bias of the Wallace--Freeman estimator
Enes Makalic, Daniel F. Schmidt
The Wallace--Freeman estimator is a classical minimum message length estimator whose relationship with likelihood-based asymptotic theory has not been fully developed. We show that…
Information Geometry and Asymptotic Theory for SMML Estimators
Enes Makalic, Daniel F. Schmidt
Strict minimum message length (SMML) is an information-theoretic coding principle that represents a continuous statistical model by a finite set of assertions and a partition of th…
MML Probabilistic Principal Component Analysis
Enes Makalic, Daniel F. Schmidt
Principal component analysis (PCA) is perhaps the most widely used method for data dimensionality reduction. A key question in PCA is deciding how many factors to retain. This manu…