coverage {DiceDesign} | R Documentation |
Coverage
Description
Compute the coverage measure
Usage
coverage(design)
Arguments
design |
a matrix (or a data.frame) representing the design of experiments representing the design of experiments in the unit cube [0,1] |
Details
The coverage criterion is defined by
where is the minimal distance between the point
and the other points of the
design
and is
the mean of the
.
Note that for a regular mesh, cov
=0. Then, a small value of cov
means that the design is close to a regular grid.
Value
A real number equal to the value of the coverage criterion for the design
.
Author(s)
J. Franco
References
Gunzburer M., Burkdart J. (2004) Uniformity measures for point samples in hypercubes, https://people.sc.fsu.edu/~jburkardt/.
See Also
other distance criteria like meshRatio
, phiP
and mindist
.
discrepancy measures provided by discrepancyCriteria
.
Examples
dimension <- 2
n <- 40
X <- matrix(runif(n*dimension), n, dimension)
coverage(X)