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Diagonally bind together subgroup-specific distances

Source: R/InfinitySparseMatrix.R
dbind.Rd

This function generates a single block-diagonal distance matrix given several distance matrices defined on subgroups.

Usage

dbind(..., force_unique_names = FALSE)

Arguments

...

Any number of distance objects which can be converted to InfinitySparseMatrix, such as class matrix, DenseMatrix, InfinitySparseMatrix, or BlockedInfinitySparseMatrix, or lists containing distance objects.

force_unique_names

Default FALSE. When row or column names are not unique among all distances, if FALSE, throw a warning and rename all rows and columns to ensure unique names. If TRUE, error on non-unique names.

Value

A BlockedInfinitySparseMatrix containing a block-diagonal 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.

Details

When you've generated several distances matrices on subgroups in your analysis, you may wish to combine them into a single block-diagonal 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("matching-within-subgroups", package = "optmatch") for details on combining multiple matches.

Examples

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)
#> [1] TRUE