Model all possible end-member scenarios.

Description

This function takes a definition of weight transformation limits and corresponding minimum and maximum numbers of end-members to model all end-member scenarios in accordance with these parameters. Based on the output the user can decide on robust end-members.

Usage

model.em(X, q, l, plot = TRUE, col.q = TRUE, bw, ...)

Arguments

Details

The plot output is an overlay of several data. The coloured lines in the background are end-member loadings (number noted in the plot title), resulting from all possible model scenarios. If col.q == TRUE they are coloured according to the number of end-members with which the model was generated. This colour scheme allows to depict end-members that emerge for model realisations with specific number of end-members. The thick black line is a kernel density estimate curve, generated from the mode positions of all end-members. The kernel bandwidth is set to 1 percent of the number of grain-size classes of the input data set, which gave useful results for most of our test data sets. The cumulaitve dot-line-plot is a further visualisation of end-member mode positions. The function is a modified wrapper function for the function test.robustness().

Value

List object with all modelled end-members, each described by input parameters, mode position, quality measures and value distributions.

Author(s)

Michael Dietze, Elisabeth Dietze

References

Dietze E, Hartmann K, Diekmann B, IJmker J, Lehmkuhl F, Opitz S, Stauch G, Wuennemann B, Borchers A. 2012. An end-member algorithm for deciphering modern detrital processes from lake sediments of Lake Donggi Cona, NE Tibetan Plateau, China. Sedimentary Geology 243-244: 169-180.

See Also

EMMA, test.l.max

Examples

## load example data set
data(X, envir = environment())

## define input parameters
l <- c(0, 0.05, 0.10)
q <- cbind(c(2, 2, 3), c(5, 6, 4))

## infer l-vector
em_pot <- model.em(X = X, q = q, l = l)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(EMMAgeo)
Loading required package: GPArotation
Loading required package: limSolve
Loading required package: shape
Loading required package: shiny
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/EMMAgeo/model.em.Rd_%03d_medium.png", width=480, height=480)
> ### Name: model.em
> ### Title: Model all possible end-member scenarios.
> ### Aliases: model.em
> ### Keywords: EMMA
> 
> ### ** Examples
> 
> ## load example data set
> data(X, envir = environment())
> 
> ## define input parameters
> l <- c(0, 0.05, 0.10)
> q <- cbind(c(2, 2, 3), c(5, 6, 4))
> 
> ## infer l-vector
> em_pot <- model.em(X = X, q = q, l = l)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>