boolean flag indicating if the transformation should include the scaling operation

scale

Given a number of (2D) configurations, this function uses a
combination of transformations (reflections, rotations,
translations and scaling) to find a 'consensus' configuration which
best matches all the component configurations in a least-squares
sense.

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.

GPA: Generalised Procrustes Analysis of configurations

Description

Usage

Arguments

Value

See Also