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OSFD (version 3.1)

mMdist: Minimax distance

Description

mMdist computes the minimax distance of a deisng in a specified region. A large uniform sample from the specified region is needed to compute the minimax distance.

Usage

mMdist(X, X_space)

Value

the minimax distance.

Arguments

X

a matrix specifying the design.

X_space

a large sample of uniform points in the space of interest.

Details

mMdist approximates the minimax distance of a set of points X by the large sample X_space in the space of interest.

References

Johnson, Mark E., Leslie M. Moore, and Donald Ylvisaker. (1990), "Minimax and Maximin Distance Designs”, Journal of Statistical Planning and Inference, 26, 131–148.

Wang, Shangkun, Adam P. Generale, Surya R. Kalidindi, and V. Roshan Joseph. (2024), "Sequential designs for filling output spaces", Technometrics, 66, 65–76.

Examples

Run this code
# the minimax distance of a random Latin hypercube design
D = randomLHS(5, 2)
mMdist(D, replicate(2, runif(1e5)))


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