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EMMAgeo (version 0.9.7)

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

190

Version

0.9.7

License

GPL-3

Maintainer

Michael Dietze

Last Published

December 16th, 2019

Functions in EMMAgeo (0.9.7)

robust.EM

Extract robust end-members
robust.scores

Extract robust end-member scores.
robust.loadings

Extract robust end-member loadings
test.factors

Calculate the initial cumulative explained variance of factors.
get.l.opt

Identify optimum weight transformation value
test.robustness

Test model robustness.
test.parameters

Evaluate influence of model parameters.
get.l

Generate a vector of weight transformation values from l.min to l.max.
interpolate.classes

Interpolate data between different classes.
mix.EM

Function to mix sample spectres.
get.limits

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

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

Find maximum possible wight transformation value.
get.q

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

Model all possible end-member scenarios
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.
click.limits

Define mode limits by mouse clicks.
GUI

Start GUI for EMMA
EMpot

example data
convert.units

Convert between phi and micrometers.
create.EM

Create grain-size-distributions.
check.data

Check correctness and consistency of input data
EMMA

End-member modelling analysis algorithm.
EMrob

example data
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example data