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Compute marginal compositions by amalgamating the rest (additively).
rcompmargin(X,d=c(1,2),name="+",pos=length(d)+1,what="data")
composition or dataset of compositions
vector containing the indices xor names of the columns to be kept
The new name of the amalgamation column
The position where the new amalgamation column should be stored. This defaults to the last column.
The role of X either "data"
for data (or means) to be
transformed or "var"
for variances to be transformed.
A closed compositions with class "rcomp"
containing the
selected variables given by d
and the the amalgamation column.
MNAR has the highest priority, MAR next and WZERO (BDL,SZ),- values are considered as 0 and reported as BDL in the End.
The amalgamation column is simply computed by adding the
non-selected components after closing the composition. This is
consistent with the rcomp
approach and is widely used because
of its easy interpretation. However, it often leads to difficult-to-read
ternary diagrams and is inconsistent with the acomp
approach.
With the argument what="var"
the function transformes an rcomp
variance to the resulting variance of the resulting composition.
References missing
# NOT RUN {
data(SimulatedAmounts)
plot.rcomp(sa.tnormals5,margin="rcomp")
plot.rcomp(rcompmargin(sa.tnormals5,c("Cd","Zn")))
plot.rcomp(rcompmargin(sa.tnormals5,c(1,2)))
# }
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