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 Infs.
The min.controls argument
given to maxControlsCap or, if none was given, a vector
of 0s;
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.