I have applied GMM(Gaussian Mixture Model) to my data set and I have plotted the resulting BIC(Bayesian Information Criterion) and AIC(Akaike Information Criterion) for different number of components. I would like to know how can I find the best heuristc number of components using BIC and AIC plots. Following paper suggests to look at the first local maxima in the plot but I do not know why? https://www.ics.uci.edu/~smyth/courses/cs274/readings/fraley_raftery.pdf
Here is the plot that I get : is lower BIC or AIC better? so I need 7 components.