Mindist measure
Compute the mindist criterion (also called maximin)
mindist(design)
design |
a matrix (or a data.frame) representing the design of experiments in the unit cube [0,1]^d. If this last condition is not fulfilled, a transformation into [0,1]^{d} is applied before the computation of the criteria. |
The mindist criterion is defined by
mindist = min (g_1, ... g_n)
where g_i is the minimal distance between the point x_i
and the other points x_k of the design.
A higher value corresponds to a more regular scaterring of design points.
A real number equal to the value of the mindist criterion for the design.
J. Franco
Gunzburer M., Burkdart J. (2004), Uniformity measures for point samples in hypercubes, https://people.sc.fsu.edu/~jburkardt/.
Jonshon M.E., Moore L.M. and Ylvisaker D. (1990), Minmax and maximin distance designs, J. of Statis. Planning and Inference, 26, 131-148.
Chen V.C.P., Tsui K.L., Barton R.R. and Allen J.K. (2003), A review of design and modeling in computer experiments, Handbook of Statistics, 22, 231-261.
other distance criteria like meshRatio and phiP,
discrepancy measures provided by discrepancyCriteria.
dimension <- 2 n <- 40 X <- matrix(runif(n*dimension), n, dimension) mindist(X)
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