Abstract:
A method is presented for assessing and statistically testing the similarity of detrital zircon U–Pb age distributions frequently used in provenance analysis, correlation and tectonic reconstructions. The method accounts for intrinsic measurement uncertainties by constructing kernel functional estimates of each set of age data that compensate for different degrees of measurement error by the application of varying levels of smoothing. The dissimilarity between these estimates can be quantified and provides a meaningful comparison between age distributions. A Monte Carlo permutation algorithm is used to test for equality between age distributions by grouping two sets of age data and then resampling the age distributions. The techniques are demonstrated with both synthetic and real data. Synthetic data illustrate the behaviour of the algorithms with data containing varying age modes and measurement uncertainties. Real data from Tasmania and southeastern Australia illustrates both the broad correlation with previous similarity assessment techniques and the applicability of the described methods to provenance, regional correlation and tectonic reconstruction.