maxControlsCap | R Documentation |
Functions to find the largest value of min.controls, or the smallest value of max.controls, for which a full matching problem is feasible. These are determined by constraints embedded in the matching problem's distance matrix.
maxControlsCap(distance, min.controls = NULL, solver = "")
minControlsCap(distance, max.controls = NULL, solver = "")
distance |
Either a matrix of non-negative, numeric
discrepancies, or a list of such matrices. (See
|
min.controls |
Optionally, set limits on the minimum number
of controls per matched set. (Only makes sense for
|
solver |
Choose which solver to use. See |
max.controls |
Optionally, set limits on the maximum number
of controls per matched set. (Only makes sense for
|
The function works by repeated application of full matching, so on large problems it can be time-consuming.
For minControlsCap
,
strictest.feasible.min.controls
and
given.max.controls
. For maxControlsCap
,
given.min.controls
and
strictest.feasible.max.controls
.
strictest.feasible.min.controls |
The largest values of the
|
given.max.controls |
The |
given.min.controls |
The |
strictest.feasible.max.controls |
The smallest values of
the |
Essentially this is just a line search. I've done several
things to speed it up, but not everything that might be done.
At present, not very thoroughly tested either: you might check
the final results to make sure that fullmatch
works with the values of min.controls
(or
max.controls
) suggested by these functions, and that it
ceases to work if you increase (decrease) those values.
Comments appreciated.
Ben B. Hansen
Hansen, B.B. and S. Olsen Klopfer (2006), ‘Optimal full matching and related designs via network flows’, Journal of Computational and Graphical Statistics 15, 609–627.
fullmatch
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