miniMaxPro: Compute minimax projection designs using clustering on...

In minimaxdesign: Minimax and Minimax Projection Designs

Description

miniMaxPro.

Usage

miniMaxPro(N,p,mMdes=NA, mMtol=1e-3*p,
          neval=1e5, itmax_refine=100, ...)

Arguments

N	Number of design points.
p	Dimension of design region.
mMdes	Minimax design from minimax().
mMtol	Tolerance for fill distance increase (actual increase may be slightly higher).
neval	Number of sample points for refinement.
itmax_refine	Maximum number of iterations for refinement.
...	Parameters for minimax().

Value

A list with two objects:

minimax	An N-by-p matrix for the minimax design.
miniMaxPro	An N-by-p matrix for the minimax projection design.

Examples

## Not run: 
#30-point miniMaxPro design on the hypercube [0,1]^6
D <- minimax(N=30,p=6)
D <- miniMaxPro(N=30,p=6,mMdes=D)
mMdist(D$minimax)$dist
mMdist(D$miniMaxPro)$dist #slightly higher fill distance
pairs(D$minimax,xlim=c(0,1),ylim=c(0,1),pch=16)
pairs(D$miniMaxPro,xlim=c(0,1),ylim=c(0,1),pch=16) #... but better projections


## End(Not run)

minimaxdesign documentation built on July 13, 2021, 1:06 a.m.