View source: R/InfinitySparseMatrix.R
dbind  R Documentation 
This function generates a single blockdiagonal distance matrix given several distance matrices defined on subgroups.
dbind(..., force_unique_names = FALSE)
... 
Any number of distance objects which can be converted to

force_unique_names 
Default 
When you've generated several distances matrices on subgroups in your
analysis, you may wish to combine them into a single blockdiagonal distance
matrix. The dbind
function facilitates this.
Any BlockedInfinitySparseMatrix
include in ...
will be broken
into individual InfinitySparseMatrix
before being joined back
together. For example, if b
is a BlockedInfinitySparseMatrix
with 2 subgroups and m
is a distance without subgroups, then
dbind(b, m)
will be a BlockedInfinitySparseMatrix
with 3
subgroups.
If there are any shared names (either row or column) among all distances
passed in, by default all matrices will be renamed to ensure unique names by
appending "X." to each distance, where "X" is ascending lower case letters
("a.", "b.", etc). Setting the force_unique_names
argument to
TRUE
errors on this instead.
If the matrices need to be renamed and there are more than 26 separate matrices, after the first 26 single "X." prefixs, they will continue as "YX.", e.g "aa.", "ab.", "ac.". If more than 676 separate matrices, the prefix wil continue to "ZYX.", e.g. "aaa.", "aab.", "aac.". This scheme supports up to 18,278 unique matrices.
Note that you do not have to combine subgroup distances into a
single blocked distance using this function to ultimately obtain a single
matching set. Instead, take a look at the vignette
vignette("matchingwithinsubgroups", package = "optmatch")
for
details on combining multiple matches.
A BlockedInfinitySparseMatrix
containing a blockdiagonal
distance matrix. If only a single distance is passed to dbind
and
it is not already a BlockedInfinitySparseMatrix
, the result will be
an InfinitySparseMatrix
instead.
data(nuclearplants)
m1 < match_on(pr ~ cost, data = subset(nuclearplants, pt == 0),
caliper = 1)
m2 < match_on(pr ~ cost, data = subset(nuclearplants, pt == 1),
caliper = 1.3)
blocked < dbind(m1, m2)
dists < list(m1, m2)
blocked2 < dbind(dists)
identical(blocked, blocked2)
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