Bayesian inference on the parameters of the truncated normal distribution and application to reverberation chamber measurement data

Assessing reverberation chambers performance is a continuous problem which requires constant development and analysis. Several performance indicators exist, have been proposed and continue to be proposed in the literature. Each one of these indicators exhibits different levels of applicability, robustness or relevance towards a particular aspect of the field (statistical) behavior inside the reverberation chamber. In this paper, we contribute to this problem by introducing an alternative methodology able to estimate the distribution of the statistical parameters of interest. The methodology is based on Bayesian inference and it is applied to two different statistical models for reverberation chambers measurement data and to two different loading conditions.