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.

Usage

maxControlsCap(distance, min.controls = NULL, solver = "")

minControlsCap(distance, max.controls = NULL, solver = "")

Arguments

distance

Either a matrix of non-negative, numeric discrepancies, or a list of such matrices. (See fullmatch for details.)

min.controls

Optionally, set limits on the minimum number of controls per matched set. (Only makes sense for maxControlsCap.)

solver

Choose which solver to use. See help(fullmatch) for details.

max.controls

Optionally, set limits on the maximum number of controls per matched set. (Only makes sense for minControlsCap.)

Value

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 fullmatch argument min.controls that yield a full match;

given.max.controls

The max.controls argument given to minControlsCap or, if none was given, a vector of Infs.

given.min.controls

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

strictest.feasible.max.controls

The smallest values of the fullmatch argument max.controls that yield a full match.

Details

The function works by repeated application of full matching, so on large problems it can be time-consuming.

Note

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.

References

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

Ben B. Hansen