test.parameters {EMMAgeo}  R Documentation 
All possible combinations of number of endmembers 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 

q 

l 

c 

rotation 

plot 

legend 

multicore 

... 
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 endmembers for subsequent modelling, e.g. as the number of
endmembers, which reaches the first local mRt maximum.
Overlapping is
defined as one endmember having its mode within the "area" of any other
endmember, which is genetically not explainable.
Keywords to specify,
which tested parameter will be plotted: "mEm" (mean absolute rowwise
error), "mEn" (mean absolute columnwise error), "mRm" (mean
relative rowwise error), "mRn" (mean relative columnwise error), "mRt"
(mean relative total error) and "ol" (number of overlapping endmembers).
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 rowwise model error. 
mEn 
Absolute columnwise model error. 
mRm 
Mean rowwise explained variance. 
mRn 
Mean columnwise explained variance. 
mRt 
Mean total explained variance. 
ol 
Number of overlapping endmember loadings. 
q.max 
Maximum number of meaningful endmembers. 
Michael Dietze, Elisabeth Dietze
Dietze E, Hartmann K, Diekmann B, IJmker J, Lehmkuhl F, Opitz S, Stauch G, Wuennemann B, Borchers A. 2012. An endmember algorithm for deciphering modern detrital processes from lake sediments of Lake Donggi Cona, NE Tibetan Plateau, China. Sedimentary Geology 243244: 169180.
## 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 endmembers
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 endmembers
TP$q.max