lapply, these functions apply a given function to each data component in
the input multiData structure, and optionally simplify the result to an array if possible.mtd.apply(multiData, FUN, ...,
mdaSimplify = FALSE, mdaCopyNonData = FALSE)mtd.applyToSubset(multiData, FUN, ...,
mdaRowIndex = NULL, mdaColIndex = NULL,
mdaSimplify = FALSE, mdaCopyNonData = FALSE)
FUN.multiData. Each element must be
a logical or numeric vector that specifies rows in each data component
to select before applying the function.data component
to select before applying the function.multiData be copied into the output?
Note that the copying is incompatible with simplification; enabling both will trigger an error.data component in the
input multiData structure. Other components are simply copied.data component. In a "strict" multiData structure, the
data components are required to each be a matrix or a data frame and have the same number of
columns. In a "loose" multiData structure, the data components can be anything (but for most
purposes should be of comparable type and content).mtd.apply works on any "loose" multiData structure; mtd.applyToSubset assumes (and checks
for) a "strict" multiData structure.
mtd.applyToSubset for applying a function to a subset of a multiData structure;
mtd.mapply for vectorizing over several arguments.