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