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EMMAgeo (version 0.9.9)

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

89

Version

0.9.9

License

GPL-3

Maintainer

Michael Dietze

Last Published

June 28th, 2025

Functions in EMMAgeo (0.9.9)

test.parameters

Evaluate influence of model parameters.
get.l

Generate a vector of weight transformation values from l.min to l.max.
robust.EM

Extract robust end-members
get.q

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

Extract robust end-member loadings
interpolate.classes

Interpolate data between different classes.
test.robustness

Test model robustness.
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.factors

Calculate the initial cumulative explained variance of factors.
mix.EM

Function to mix sample spectres.
click.limits

Define mode limits by mouse clicks.
EMpot

example data
EMrob

example data
check.data

Check correctness and consistency of input data
convert.units

Convert between phi and micrometers.
create.EM

Create grain-size-distributions.
get.l.opt

Identify optimum weight transformation value
GUI

Start GUI for EMMA
EMMA

End-member modelling analysis algorithm.
X

example data
EMMAgeo-package

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

Calculate a residual end-member loading.
model.EM

Model all possible end-member scenarios
get.limits

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