Statistical Toolbox for Sedimentary Provenance Analysis
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Documentation for package ‘provenance’ version 4.4
Help Pages
| provenance-package | Menu-based interface for 'provenance' |
| ALR | Additive logratio transformation |
| ALR.compositional | Additive logratio transformation |
| ALR.default | Additive logratio transformation |
| amalgamate | Group components of a composition |
| amalgamate.compositional | Group components of a composition |
| amalgamate.counts | Group components of a composition |
| amalgamate.default | Group components of a composition |
| amalgamate.SRDcorrected | Group components of a composition |
| amalgamate.varietal | Group components of a composition |
| as.acomp | create an 'acomp' object |
| as.compositional | create a 'compositional' object |
| as.counts | create a 'counts' object |
| as.data.frame | create a 'data.frame' object |
| as.data.frame.compositional | create a 'data.frame' object |
| as.data.frame.counts | create a 'data.frame' object |
| as.varietal | create a 'varietal' object |
| botev | Compute the optimal kernel bandwidth |
| bray.diss | Bray-Curtis dissimilarity |
| bray.diss.compositional | Bray-Curtis dissimilarity |
| bray.diss.default | Bray-Curtis dissimilarity |
| CA | Correspondence Analysis |
| central.counts | Calculate central compositions |
| CLR | Centred logratio transformation |
| CLR.compositional | Centred logratio transformation |
| CLR.default | Centred logratio transformation |
| combine | Combine samples of distributional data |
| densities | A list of rock and mineral densities |
| diss.compositional | Calculate the dissimilarity matrix between two datasets of class 'distributional', 'compositional', 'counts' or 'varietal' |
| diss.counts | Calculate the dissimilarity matrix between two datasets of class 'distributional', 'compositional', 'counts' or 'varietal' |
| diss.distributional | Calculate the dissimilarity matrix between two datasets of class 'distributional', 'compositional', 'counts' or 'varietal' |
| diss.varietal | Calculate the dissimilarity matrix between two datasets of class 'distributional', 'compositional', 'counts' or 'varietal' |
| 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 level of sampling resolution |
| get.p | Calculate the probability of missing a given population fraction |
| 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 |
| KS.diss.default | Kolmogorov-Smirnov dissimilarity |
| KS.diss.distributional | Kolmogorov-Smirnov dissimilarity |
| Kuiper.diss | Kuiper dissimilarity |
| Kuiper.diss.default | Kuiper dissimilarity |
| Kuiper.diss.distributional | Kuiper dissimilarity |
| lines | Ternary point plotting |
| lines.ternary | Ternary line plotting |
| MDS | Multidimensional Scaling |
| MDS.compositional | Multidimensional Scaling |
| MDS.counts | Multidimensional Scaling |
| MDS.default | Multidimensional Scaling |
| MDS.distributional | Multidimensional Scaling |
| MDS.varietal | Multidimensional Scaling |
| minsorting | Assess settling equivalence of detrital components |
| Namib | An example dataset |
| PCA | Principal Component Analysis |
| plot.CA | Point-counting biplot |
| plot.compositional | Plot a pie chart |
| plot.distributional | Plot continuous data as histograms or cumulative age distributions |
| plot.GPA | Plot a Procrustes configuration |
| plot.INDSCAL | Plot an INDSCAL group configuration and source weights |
| plot.KDE | Plot a kernel density estimate |
| plot.KDEs | Plot one or more kernel density estimates |
| plot.MDS | Plot an MDS configuration |
| plot.minsorting | Plot inferred grain size distributions |
| plot.PCA | Compositional biplot |
| plot.ternary | Plot a ternary diagram |
| points.ternary | Ternary point plotting |
| procrustes | Generalised Procrustes Analysis of provenance data |
| provenance | Menu-based interface for 'provenance' |
| radialplot.counts | Visualise point-counting data on a radial plot |
| read.compositional | Read a .csv file with compositional data |
| read.counts | Read a .csv file with point-counting data |
| read.densities | Read a .csv file with mineral and rock densities |
| read.distributional | Read a .csv file with distributional data |
| read.varietal | Read a .csv file with varietal data |
| restore | Undo the effect of hydraulic sorting |
| SH.diss | Sircombe and Hazelton distance |
| SNSM | varietal data example |
| subset | Get a subset of provenance data |
| subset.compositional | Get a subset of provenance data |
| subset.counts | Get a subset of provenance data |
| subset.distributional | Get a subset of provenance data |
| subset.varietal | Get a subset of provenance data |
| summaryplot | Joint plot of several provenance datasets |
| ternary | Define a ternary composition |
| ternary.ellipse | Ternary confidence ellipse |
| ternary.ellipse.compositional | Ternary confidence ellipse |
| ternary.ellipse.counts | Ternary confidence ellipse |
| ternary.ellipse.default | Ternary confidence ellipse |
| text | Ternary point plotting |
| text.ternary | Ternary text plotting |
| varietal2distributional | Convert varietal to distributional data |
| Wasserstein.diss | Wasserstein distance |
| Wasserstein.diss.default | Wasserstein distance |
| Wasserstein.diss.distributional | Wasserstein distance |
| Wasserstein.diss.varietal | Wasserstein distance |