doALS2.RdThis function is the same as doALS from package alsace (version 1.6.0), just with more possible input parameters, which are passed to als from package ALS.
doALS2(
Xl,
PureS,
maxiter = 100,
normS = 0.5,
uniC = FALSE,
uniS = FALSE,
nonnegS = TRUE,
nonnegC = TRUE,
optS1st = FALSE,
baseline = FALSE,
closureC = list(),
...
)a list of (numerical) data matrices. Missing values are not allowed.
Initial estimates of pure spectral components.
The maximum number of iterations to perform (where an
iteration is optimization of either AList and C)
numeric indicating whether the spectra are normalized; if
normS>0, the spectra are normalized. If normS==1 the
maximum of the spectrum of each component is constrained to be equal
to one; if normS > 0 && normS!=1 then the norm of the
spectrum of each component is constrained to be equal to one.
logical indicating whether unimodality constraints should be
applied to the columns of C
logical indicating whether unimodality constraints should be
applied to the columns of S
logical indicating whether the components (columns) of
the matrix S should be constrained to non-negative values
logical indicating whether the components (columns) of
the matrix C should be constrained to non-negative values
logical indicating whether the first constrained least
squares regression should estimate S or CList.
logical indicating whether a baseline component is
present; if baseline=TRUE then this component is exempt from
constraints unimodality or non-negativity
list; if the length is zero, then no closure constraints are applied. If the length is not zero, it should be equal to the number of datasets in the analysis, and contain numeric vectors consisting of the desired value of the sum of each row of the concentration matrix.
Other parametars to be passed to function als.
The same as in doALS.
# /NO examples YET/