A popular approach for testing if two univariate random variables are statistically independent consists of partitioning the sample space into bins, and evaluating a test statistic on the binned data. The partition size matters, and the optimal partition size is data dependent. While for detecting simple relationships coarse partitions may be best, for detecting complex relationships a great ga...

This paper attempts the well-known regularized gamma distribution function to represent the separation efficiency of particle segregation in gravity concentrators. The model has four parameters that are evaluated by a least square fit between the model estimate and the measured data. The model takes into account the bivariate effects of particle size and particle density to define the size-dens...

Stratification is one of the most widely used techniques in finite population sampling. Strata are disjoint subdivisions of a population, the union of which exhaust the universe, each of which contains a portion of the sample. Two of its essential statistical purposes are to: (1) allow for efficient estimation, especially in the case of stratification by size, and (2) deal statistically with su...

The study of partition statistics can be said to have begun with Erdős and Lehner [3] in 1941, who studied questions concerning the normal, resp. average value over all partitions of n of quantities such as the number of parts, the number of different part sizes, and the size of the largest part. To begin with, instead of looking at parts in partitions we will look at gaps, that is, at part siz...

In this paper we present experiments with a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then uncoarsen it to construct a partition for the original graph. We investigate the effectiveness of many different choices for all three phases: coarsening, partition of the coarsest graph, and refinement. In p...