provenance: Statistical Toolbox for Sedimentary Provenance Analysis

Bundles a number of established statistical methods to facilitate the visual interpretation of large datasets in sedimentary geology. Includes functionality for adaptive kernel density estimation, multidimensional scaling, generalised procrustes analysis and individual differences scaling using a variety of dissimilarity measures. Univariate provenance proxies, such as single-grain ages or (isotopic) compositions are compared with the Kolmogorov- Smirnov dissimilarity and Sircombe-Hazelton L2-norm. Categorical provenance proxies, such as mineralogical, petrographic or chemical compositions are compared with the Aitchison and Bray-Curtis distances. Also included are tools to plot compositional data on ternary diagrams, to calculate the sample size required for specified levels of statistical precision, and to assess the effects of hydraulic sorting on detrital compositions. Includes an intuitive query-based user interface for users who are not proficient in R.

AuthorPieter Vermeesch [aut, cre]
Date of publication2016-04-22 08:40:10
MaintainerPieter Vermeesch <p.vermeesch@ucl.ac.uk>
LicenseGPL-2
Version1.5

View on CRAN

Man pages

amalgamate: Group components of a composition

as.acomp: create an 'acomp' object

as.compositional: create a 'compositional' object

as.data.frame.compositional: create a 'data.frame' object

botev: Compute the optimal kernel bandwidth

bray.diss: Bray-Curtis dissimilarity

CLR: Centred logratio transformation

combine: Combine samples of distributional data

densities: A list of rock and mineral densities

diss: Calculate the dissimilarity matrix between two...

endmembers: Petrographic end-member compositions

get.f: Calculate the largest fraction that is likely to be missed

get.n: Calculate the number of grains required to achieve a desired...

get.p: Calculate the probability of missing a given population...

GPA: Generalised Procrustes Analysis of configurations

indscal: Individual Differences Scaling of provenance data

KDE: Create a kernel density estimate

KDEs: Generate an object of class 'KDEs'

KS.diss: Kolmogorov-Smirnov dissimilarity

MDS: Multidimensional Scaling

minsorting: Assess settling equivalence of detrital components

Namib: An example dataset

PCA: Principal Component Analysis

plot.compositional: Plot a pie chart

plot.distributional: Plot continuous data as histograms or cumulative age...

plot.GPA: Plot a Procrustes configuration

plot.INDSCAL: Plot an INDSCAL group configuration and source weights

plot.KDE: Plot a kernel density estimate

plot.MDS: Plot an MDS configuration

plot.minsorting: Plot inferred grain size distributions

plot.PCA: Compositional biplot

plot.ternary: Plot a ternary diagram

procrustes: Generalised Procrustes Analysis of provenance data

provenance: Menu-based interface for 'provenance'

read.compositional: Read a .csv file with categorical data

read.densities: Read a .csv file with mineral and rock densities

read.distributional: Read a .csv file with continuous (detrital zircon) data

restore: Undo the effect of hydraulic sorting

SH.diss: Sircombe and Hazelton distance

subset.compositional: Get a subset of compositional data

subset.distributional: Get a subset of distributional data

summaryplot: Joint plot of several provenance datasets

ternary: Define a ternary composition

Files in this package

provenance
provenance/inst
provenance/inst/Trace.csv
provenance/inst/PT.csv
provenance/inst/DZ.csv
provenance/inst/endmembers.csv
provenance/inst/DZerr.csv
provenance/inst/Major.csv
provenance/inst/densities.csv
provenance/inst/PTHM.csv
provenance/inst/HM.csv
provenance/NAMESPACE
provenance/data
provenance/data/densities.rda
provenance/data/endmembers.rda
provenance/data/Namib.rda
provenance/R
provenance/R/botev.R provenance/R/provenance.R provenance/R/plot.R provenance/R/indscal.R provenance/R/minsorting.R provenance/R/documentation.R provenance/R/kde.R provenance/R/srd.R provenance/R/gui.R provenance/R/sircombe.R
provenance/MD5
provenance/DESCRIPTION
provenance/man
provenance/man/minsorting.Rd provenance/man/provenance.Rd provenance/man/ternary.Rd provenance/man/Namib.Rd provenance/man/combine.Rd provenance/man/subset.distributional.Rd provenance/man/KDEs.Rd provenance/man/as.acomp.Rd provenance/man/as.data.frame.compositional.Rd provenance/man/plot.GPA.Rd provenance/man/plot.MDS.Rd provenance/man/plot.minsorting.Rd provenance/man/bray.diss.Rd provenance/man/SH.diss.Rd provenance/man/plot.compositional.Rd provenance/man/get.p.Rd provenance/man/CLR.Rd provenance/man/diss.Rd provenance/man/plot.ternary.Rd provenance/man/densities.Rd provenance/man/endmembers.Rd provenance/man/indscal.Rd provenance/man/botev.Rd provenance/man/amalgamate.Rd provenance/man/KDE.Rd provenance/man/read.compositional.Rd provenance/man/summaryplot.Rd provenance/man/GPA.Rd provenance/man/get.n.Rd provenance/man/plot.PCA.Rd provenance/man/read.densities.Rd provenance/man/as.compositional.Rd provenance/man/PCA.Rd provenance/man/plot.distributional.Rd provenance/man/plot.INDSCAL.Rd provenance/man/get.f.Rd provenance/man/restore.Rd provenance/man/procrustes.Rd provenance/man/MDS.Rd provenance/man/read.distributional.Rd provenance/man/KS.diss.Rd provenance/man/subset.compositional.Rd provenance/man/plot.KDE.Rd

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