robust.EM {EMMAgeo}  R Documentation 
This function takes a list object with potential endmember loadings and extracts those with modes in specified limits to describe them by mean and standard deviation and use these descriptions to propagate the uncertainties to endmember scores.
robust.EM(
em,
limits,
classunits,
amount,
l,
mc_n,
type = "mean",
qt = c(0.25, 0.75),
cores = 1,
plot = FALSE,
...
)
em 

limits 

classunits 

amount 

l 

mc_n 

type 

qt 

cores 

plot 

... 
Additional arguments passed to 
The function is used to extract potential endmember loadings based on their
mode positions and, optionally the height of the mode class, and use them to
infer mean and stanard deviation of all
endmembers that match the group criteria defined by limits
. These
information are then used to model the uncertainty of the corresponding
endmember scores. The function uses input from two preceeding approaches.
In a compact protocol model.em
delivers these data in a predefined
way. In the extended protocol test.robustness
does this.
List
with statistic descriptions of endmember loadings
and scores.
Michael Dietze, Elisabeth Dietze
robust.loadings
, robust.scores
## Not run:
## load example data set
data(example_X)
## get weight transformation limit vector
l < get.l(X = X)
## get minimum and maximum number of endmembers
q < get.q(X = X, l = l)
## get all potential model scenarios
EM_pot < model.EM(X = X, q = q, plot = TRUE)
## define endmember mode class limits
limits < cbind(c(61, 74, 95, 102),
c(64, 76, 100, 105))
## get robust endmembers in the default way, with plot output
rem < robust.EM(em = EM_pot,
limits = limits,
plot = TRUE)
## get robust endmembers by only modelling uncertainty in loadings
robust_EM < robust.EM(em = EM_pot,
limits = limits,
plot = TRUE)
## End(Not run)