Parameterization of Particle Size Distributions by Three Methods

While the analysis and description of mass-frequency particle size distributions has long been of academic interest in sedimentology such analysis is of considerable economic importance in the commercial recovery of ores and in the handling of mine tailings. An important step in understanding the process of mineral separation and transport is constructing an accurate parametric model of the analysis of the mass-frequency particle size data. Two methods for estimating parametric model parameters already exist (i) the Kullback–Leibler (KL) “distance” function method and (ii) the minimum chi-square (MC) method. During the course of this investigation a third method was developed, the “maximum asymptotic likelihood (MAL) method.” The three methods were compared by application to a practical data set. This comparison demonstrated that the minimum chi-square method is, the most promising of the three.