An R package for statistical provenance analysis
By Pieter Vermeesch, Alberto Resentini, Eduardo Garzanti. 2016
414 citations recorded by the source corpus.
Abstract This paper introduces provenance, a software package within the statistical programming environment R, which aims to facilitate the visualisation and interpretation of large amounts of sedimentary provenance data, including mineralogical, petrographic, chemical and isotopic provenance proxies, or any combination of these. provenance comprises functions to: (a) calculate the sample size required to achieve a given detection limit; (b) plot distributional data such as detrital zircon U–Pb age spectra as Cumulative Age Distributions (CADs) or adaptive Kernel Density Estimates (KDEs); (c) plot compositional data as pie charts or ternary diagrams; (d) correct the effects of hydraulic sorting on sandstone petrography and heavy mineral composition; (e) assess the settling equivalence of detrital minerals and grain-size dependence of sediment composition; (f) quantify the dissimilarity between distributional data using the Kolmogorov–Smirnov and Sircombe–Hazelton distances, or between compositional data using the Aitchison and Bray–Curtis distances; (e) interpret multi-sample datasets by means of (classical and nonmetric) Multidimensional Scaling (MDS) and Principal Component Analysis (PCA); and (f) simplify the interpretation of multi-method datasets by means of Generalised Procrustes Analysis (GPA) and 3-way MDS. All these tools can be accessed through an intuitive query-based user interface, which does not require knowledge of the R programming language. provenance is free software released under the GPL-2 licence and will be further expanded based on user feedback.
Subfields: Artificial Intelligence, Environmental Engineering, Mechanics of Materials
View Paper: https://www.semanticscholar.org/paper/edac6605e132a8acc977e224f968cb96ebf55bd6
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In Artificial Intelligence
In Environmental Engineering
In Mechanics of Materials
Citations in the corpus
- IsoplotR: A free and open toolbox for geochronology (2018, methodology): “Additional options and higher order alternatives to these MDS algorithms are provided in a separate R-package called provenance (Vermeesch et al., 2016).”