Point process statistics improves particle size analysis

Abstract This paper re-considers the foundations of particle size statistics. While traditional statistics consider their data as samples random variables and use methods classical mathematical statistics, here a sample is treated point process sample, suitable form recommended. The whole sequence ordered sizes considered variable in space. Instead distribution functions, intensity functions are used. application analysis demonstrated for fragments from single-particle crushing glass balls. Three cases handling with processes presented: oversize particles, pooling independent piecewise data. Finally, problem goodness-of-fit testing briefly discussed. approach turns out to be an extension approach, simpler more elegant, but retains all valuable ideas. It particularly strong particles. Graphical abstract