R maximin_cplus
Compute the maximin criterion (also called mindist). This function uses a C++ implementation of the function mindist from package DiceDesign.
maximin_cplus is located in package sensitivity. Please install and load package sensitivity before use.
maximin_cplus(design)
design
a matrix 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.
install.packages("sensitivity", repo="http://cran.r-project.org", dep=T)
library(sensitivity)
dimension <- 2
n <- 40
X <- matrix(runif(n*dimension),n,dimension)
maximin_cplus(X)
Return Values: A real number equal to the value of the maximin criterion for the design.
Details: The maximin criterion is defined by:
maximin = 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.
See Also: discrepancy measures provided by discrepancyCriteria_cplus.
References: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.
