Modelling mass-size particle data by finite mixtures

Abstract

A minimum distance procedure, analogous to maximum likelihood for multinomial data, is employed to fit mixture models to mass-size relative frequencies recorded for some clay soils of southeastern Australia. Log hyperbolic component distributions are considered initially and it is shown how they can be fitted satisfactorily at least to ungrouped data using a generalized EM algorithm. A computationally more convenient model with log skew Laplace components is subsequently shown to suffice. It is demonstrated how it can be fitted to the data in their original grouped form. Consideration is given also to the provision of standard errors using the idea of a quasi-sample size.