269 citations · 335 across the 12 of their papers we have counts for
5 papers · 1 filter
Sparse Horseshoe Estimation via Expectation-Maximisation
Shu Yu Tew, Daniel F. Schmidt, Enes Makalic
The horseshoe prior is known to possess many desirable properties for Bayesian estimation of sparse parameter vectors, yet its density function lacks an analytic form. As such, it…
Introduction to minimum message length inference
Enes Makalic, Daniel F. Schmidt
The aim of this manuscript is to introduce the Bayesian minimum message length principle of inductive inference to a general statistical audience that may not be familiar with info…
Minimum message length inference of the Weibull distribution with complete and censored data
Enes Makalic, Daniel F. Schmidt
The Weibull distribution, with shape parameter and scale parameter , is one of the most popular parametric distributions in survival analysis with complete or censored d…
Maximum likelihood estimation of the Weibull distribution with reduced bias
Enes Makalic, Daniel F. Schmidt
In this short note, we derive a new bias adjusted maximum likelihood estimate for the shape parameter of the Weibull distribution with complete data and type I censored data. The p…
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…