Take a vector fobs of assembly performances
over several experiments
and return a vector of performances
predicted as the mean performances of assemblages
that share the same assembly motif.
Assembly motifs are labelled in the vector assMotif.
Experiments are labelled in the vector xpr.
Modelling options are indicated in opt.mean and opt.model.
Occurrence matrix mOccur is used if opt.model = "byelt".
calibrate_byminrss(fobs, assMotif, mOccur, xpr,
opt.mean = "amean", opt.model = "bymot" )a numeric vector. The vector fobs contains the
quantitative performances of assemblages.
a vector of labels of length(fobs).
The vector assMotif contains the assembly motifs of assemblages.
a matrix of occurrence (occurrence of components).
Its first dimension equals to length(fobs). Its second dimension
equals to the number of components.
a vector of numerics of length(fobs).
The vector xpr contains the weight of each experiment,
and the labels (in names(xpr)) of different experiments.
The weigth of each experiment is used
in the computation of the Residual Sum of Squares
in the function rss_clustering.
All assemblages that belong to a given experiment
should then have a same weigth.
Each experiment is identified by its names (names(xpr))
and the RSS of each experiment is weighted by values of xpr.
The vector xpr is generated
by the function stats::setNames.
a character equals to "amean" or "gmean".
Switchs to arithmetic formula if opt.mean = "amean".
Switchs to geometric formula if opt.mean = "gmean".
a character equals to "bymot" or "byelt".
Switchs to simple mean by assembly motif if opt.model = "bymot".
Switchs to linear model with assembly motif if opt.model = "byelt".
Return a vector of length(fobs).
Its values are computed according to opt.mean and opt.model.
Modelled performances are computed
using arithmetic mean (opt.mean = "amean")
or geometric mean (opt.mean = "gmean").
If opt.model = "bymot",
modelled performances are means
of performances of assemblages
that share a same assembly motif
by including all assemblages that belong to a same assembly motif.
If opt.model = "byelt",
modelled performances are the average
of mean performances of assemblages
that share a same assembly motif
and that contain the same components
as the assemblage to calibrate.
This procedure corresponds to a linear model within each assembly motif
based on the component occurrence in each assemblage.
If no assemblage contains component belonging to assemblage to calibrate,
performance is the mean performance of all assemblages
as in opt.model = "bymot".
validate_using_cross_validation
predicts performances of assemblages.