test.parameters: Evaluate influence of model parameters.
In coffeemuggler/EMMAgeo: End-Member Modelling of Grain-Size Data

Description Usage Arguments Details Value Author(s) References See Also Examples

All possible combinations of number of end-members and weight transformation limits are used to perform EMMA and evaluate the absolute and relative measures of individual model performance.

test.parameters(
  X,
  q,
  l = 0,
  c = 100,
  rotation = "Varimax",
  plot = FALSE,
  legend,
  multicore = FALSE,
  ...
)

`X`	`Numeric` matrix, input data set with m samples (rows) and n variables (columns).
`q`	`Numeric` vector, numbers of end-members to be modelled, e.g., `2:10`.
`l`	`Numeric` vector specifying the weight tranformation limit, i.e. quantile; default is 0.
`c`	`Numeric` scalar specifying the constant sum scaling parameter, e.g., 1, 100, 1000; default is 0.
`rotation`	`Character` scalar, rotation type, default is `"Varimax"`.
`plot`	`Character` scalar, optional graphical output of the results as keyword (see details). All plots except "ol" are colour-coded bitmaps of q, l and the specified test parameter and line-plots the specified parameter vs. `q`.
`legend`	`Character` scalar, specifying legend position (cf. `legend`). If omitted, no legend will be plotted, default is no legend.
`multicore`	`Logical` scalar, optionally ditribute calculations to all available cores of the computer, default is `TRUE`.
`...`	Additional arguments passed to the plot function (see details).

The mean total explained variance mRt may be used to define a maximum number of meaningful end-members for subsequent modelling, e.g. as the number of end-members, which reaches the first local mRt maximum.
Overlapping is defined as one end-member having its mode within the "area" of any other end-member, which is genetically not explainable.
Keywords to specify, which tested parameter will be plotted: "mEm" (mean absolute row-wise error), "mEn" (mean absolute column-wise error), "mRm" (mean relative row-wise error), "mRn" (mean relative column-wise error), "mRt" (mean relative total error) and "ol" (number of overlapping end-members).
Since the function returns two plots (except for option "ol"), additional graphical parameters must be specified as vector with the first element for the first plot and the second element for the second plot. If graphical parameters are natively vectors (e.g. a sequence of colours), they must be specified as matrices with each vector as a row. A legend can only be added to the second plot. Colours only apply to the second plot as well. If colours are specified, colour should be used instead of col. See example section for further advice.

List with result objects

`mEm`	Absolute row-wise model error.
`mEn`	Absolute column-wise model error.
`mRm`	Mean row-wise explained variance.
`mRn`	Mean column-wise explained variance.
`mRt`	Mean total explained variance.
`ol`	Number of overlapping end-member loadings.
`q.max`	Maximum number of meaningful end-members.

Michael Dietze, Elisabeth Dietze

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.

EMMA

## load example data set
data(example_X)

## truncate the data set for faster computation
X.trunc <- X[1:20,]

## define test parameters
q <- 2:8 # number of end-members
l <- seq(from = 0, to = 0.3, by = 0.1)

## test parameter influence and plot mean total explained variance
TP <- test.parameters(X = X.trunc, q = q, l = l, plot = "mRt",
                      legend = "bottomright", cex = 0.7,
                      multicore = FALSE,
                      colour = rgb((1:7) / 7, 0.9, 0.2, 1))

## show maximum number of end-members
TP$q.max