get.q {EMMAgeo}  R Documentation 
This function uses the input data matrix X
and a vector of weight
transformation limits to generate a matrix of minimum and maximum likely
numbers of endmembers to be used to model and extract robust endmembers.
get.q(
X,
l = 0,
q.min = 2,
q.max = 10,
criteria.min = 0.5,
criteria.max = "local_max",
correct.output = TRUE,
...
)
X 

l 

q.min 

q.max 

criteria.min 

criteria.max 

correct.output 

... 
Further arguments, passed to the function. 
The parameter q.min
should be at least 2 because otherwise the
entire dataset would consist of one endmember and there would be no
variability at all. The parameter q.max
is set to 10 by default,
based on practical issues. In natural systems, there are only rarely
occasions when such a high number of sediment transport regimes may be
preserved in and can be resolved from sedimentary deposits. The parameter
l
should be a vector between the minimum possible (zero) and maximum
possible value (by definition the median, 0.5, but usually a lower value).
Whensubmitting only a scalar, the variability can be only due to the range
of possible endmembers (between q.min
and q.max
). If the
parameter correct.output
is enabled, this can decrease the number of
valid values for l
, i.e. the number of rows of the output matrix
may no longer be the same as the length of the input vector of l
. In
such a case the vector l
must be replaced by the rownames of the
output matrix (l < as.numeric(rownames(get.q()))
).
Numeric
matrix of class "EMMAgeo_q"
, minimum and
maximum numbers of endmembers as well as corresponding weight
transformation values as rownames.
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.
EMMA
, test.parameters
,
test.robustness
## load example data set
data("example_X")
## create parameter matrix
get.q(X = X, l = c(0, 0.05, 0.10, 0.15))