  We present recent results and technical breakthroughs for the Bayesian
inference of tokamak equilibria using force-balance as a prior constraint.
Issues surrounding model parameter representation and posterior analysis are
discussed and addressed. These points motivate the recent advancements embodied
in the Bayesian Equilibrium Analysis and Simulation Tool (BEAST) software being
presently utilised to study equilibria on the Mega-Ampere Spherical Tokamak
(MAST) experiment in the UK (von Nessi \emph{et. al.} 2012 \emph{J. Phys. A}
\textbf{46} 185501). State-of-the-art results of using BEAST to study MAST
equilbria are reviewed, with recent code advancements being systematically
presented though out the manuscript.
