On the visualisation of detrital age distributions

Since the development of SIMS and LA-ICP-MS technologies in the 1980s and 1990s, single grain U–Pb dating of detrital zircon has quickly become the most popular technique for sedimentary provenance studies. Currently by far the most widespread method for visualising detrital age distributions is the so-called Probability Density Plot (PDP), which is calculated by summing a number of Gaussian distributions whose means and standard deviations correspond to the individual ages and their respective analytical uncertainties. Unfortunately, the PDP lacks a firm theoretical basis and can produce counter-intuitive results when data quantity (number of analyses) and/or quality (precision) is high. As a more robust alternative to the PDP, this paper proposes a standard statistical technique called Kernel Density Estimation (KDE), which also involves summing a set of Gaussian distributions, but does not explicitly take into account the analytical uncertainties. The Java-based DensityPlotter program (http://densityplotter.london-geochron.com) was developed with the aim to facilitate the adoption of KDE plots in the context of detrital geochronology. ► Probability Density Plots' (PDPs) are currently the most popular way of visualising detrital age distributions. ► Despite their name, PDPs have no statistical basis as a probability density estimator. ► Kernel Density Estimates (KDEs) are a theoretically sound alternative to PDPs. ► DensityPlotter is a new Java application for plotting detrital age distributions as KDEs.