The methodology of Bayesian Model Averaging (BMA) is applied for assessment
of newborn brain maturity from sleep EEG. In theory this methodology provides
the most accurate assessments of uncertainty in decisions. However, the
existing BMA techniques have been shown providing biased assessments in the
absence of some prior information enabling to explore model parameter space in
details within a reasonable time. The lack in details leads to disproportional
sampling from the posterior distribution.