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EMMAgeo (version 0.9.10)

End-Member Modelling of Grain-Size Data

Description

End-member modelling analysis of grain-size data is an approach to unmix a data set's underlying distributions and their contribution to the data set. EMMAgeo provides deterministic and robust protocols for that purpose.

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Version

Install

install.packages('EMMAgeo')

Monthly Downloads

265

Version

0.9.10

License

GPL-3

Maintainer

Michael Dietze

Last Published

July 20th, 2026

Functions in EMMAgeo (0.9.10)

EMrob

example data
GUI

Start GUI for EMMA
residual.EM

Calculate a residual end-member loading.
robust.loadings

Extract robust end-member loadings
EMpot

example data
model.EM

Model all possible end-member scenarios
convert.units

Convert between phi and micrometers.
get.l.opt

Identify optimum weight transformation value
get.limits

Infer lower and upper mode position limits to define robust end-members.
check.data

Check correctness and consistency of input data
interpolate.classes

Interpolate data between different classes.
get.l

Generate a vector of weight transformation values from l.min to l.max.
get.q

Generate a parameter matrix with q.min and q.max values for robust EMMA.
EMMA

End-member modelling analysis algorithm.
mix.EM

Function to mix sample spectres.
create.EM

Create grain-size-distributions.
robust.EM

Extract robust end-members
X

example data
click.limits

Define mode limits by mouse clicks.
test.factors

Calculate the initial cumulative explained variance of factors.
robust.scores

Extract robust end-member scores.
test.l

Test a vector of weight transformation limits for mximum value.
test.l.max

Find maximum possible wight transformation value.
test.parameters

Evaluate influence of model parameters.
test.robustness

Test model robustness.
EMMAgeo-package

End-member modelling algorithm and supporting functions for unmixing grain-size distributions and further compositional data.