plot.minsorting

Plot the grain size distributions of the different minerals under
consideration

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, principal component analysis, correspondence analysis, 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, Kuiper, Wasserstein-2 or Sircombe-Hazelton L2 distances. Categorical provenance proxies such as chemical compositions are compared with the Aitchison and Bray-Curtis distances,and count data with the chi-square distance. Varietal data can either be converted to one or more distributional datasets, or directly compared using the multivariate Wasserstein distance. Also included are tools to plot compositional and count data on ternary diagrams and point-counting data on radial plots, 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.

Pieter Vermeesch

provenance

Statistical Toolbox for Sedimentary Provenance Analysis

plot.minsorting function

<dl><dt>x</dt>
<dd>an object of class <code>minsorting</code></dd>
<dt>cumulative</dt>
<dd>boolean flag indicating whether the grain size
distribution should be plotted as a density or cumulative
probability curve.</dd>
<dt>components</dt>
<dd>string or list of strings with the names of a
subcomposition that needs plotting</dd>
<dt>...</dt>
<dd>optional parameters to be passed on to graphics::matplot
(see <code><a href="/link/%3Fpar?package=provenance&version=4.4" data-mini-rdoc="provenance::?par">?par</a></code> for details)</dd></dl>

Arguments

Plot inferred grain size distributions — plot.minsorting

<dl>

<dt>x</dt>
<dd>an object of class <code>minsorting</code></dd>


<dt>cumulative</dt>
<dd>boolean flag indicating whether the grain size
distribution should be plotted as a density or cumulative
probability curve.</dd>


<dt>components</dt>
<dd>string or list of strings with the names of a
subcomposition that needs plotting</dd>


<dt>...</dt>
<dd>optional parameters to be passed on to graphics::matplot
(see <code><a href='https://rdrr.io/r/graphics/par.html'>?par</a></code> for details)</dd>

</dl>

plot.minsorting: Plot inferred grain size distributions

Description

Usage

Arguments

See Also

Examples