Bayesian model comparison and selection in energy decay analysis of acoustically coupled spaces

Abstract

The use of Bayesian inference in problems of parameter estimation from noisy data and in uncertain environments has been well discussed in the acoustical signal processing literature. In many acoustical problems where it is uncertain which suitable model among a set of competing ones should be used, the model comparison and selection become crucial prior to the actual parameter estimation. However, tools for model selection in Bayesian inference have received less attention. In problems of model comparison and selection, the Bayesian methodology is most different from orthodox statistical methods. We present several methods for model comparison and selection from a Bayesian viewpoint and demonstrate their application to the problem of estimating the number of decay rates present in acoustically coupled spaces.