Rufo, M.J.; Martín, J.; Pérez, C.J. - In: Computational Statistics & Data Analysis 54 (2010) 12, pp. 3324-3335
Two new approaches to estimate Bayes factors in a finite mixture model context are proposed. Specifically, two algorithms to estimate them and their errors are derived by decomposing the resulting marginal densities. Then, through Bayes factor comparisons, the appropriate number of components...