Description Usage Arguments Details Value Author(s) References See Also Examples

Compute the coverage measure

1 | ```
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)
=1/gMean *[ 1/n * [( g_1 - gMean )^2 + ... + (g_n - gMean)^2] ]^(1/2)*

where *g_i* is the minimal distance between the point *x_i*
and the other points of the `design`

and *gMean* is
the mean of the *g_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`

.

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