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)minControlsCap(distance, max.controls = NULL)
Either a matrix of non-negative, numeric
discrepancies, or a list of such matrices. (See
fullmatch
for details.)
Optionally, set limits on the minimum number
of controls per matched set. (Only makes sense for
maxControlsCap
.)
Optionally, set limits on the maximum number
of controls per matched set. (Only makes sense for
minControlsCap
.)
For minControlsCap
,
strictest.feasible.min.controls
and
given.max.controls
. For maxControlsCap
,
given.min.controls
and
strictest.feasible.max.controls
.
The largest values of the
fullmatch
argument min.controls
that yield
a full match;
The max.controls
argument
given to minControlsCap
or, if none was given, a vector
of Inf
s.
The min.controls
argument
given to maxControlsCap
or, if none was given, a vector
of 0
s;
The smallest values of
the fullmatch
argument max.controls
that
yield a full match.
The function works by repeated application of full matching, so on large problems it can be time-consuming.
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.