phiP {DiceDesign} R Documentation

## phiP criterion

### Description

Compute the \phi_p criterion (strongly linked to mindist criterion)

### Usage

phiP(design, p=50)

### Arguments

 design a matrix (or a data.frame) corresponding to the design of experiments. p the "p" in the Lp norm which is taken

### Details

The \phi_p criterion is defined by the L_p norm of the sum of the inverses of the design inter-point euclidean distances:

\phi_{p}=\left[\sum_{i,j=1\ldots N,i<j}\,\,d_{ij}^{-p}\right]^{\frac{1}{p}}

A higher value corresponds to a more regular scaterring of design points.

When p tends to infinity, optimizing a design with \phi_p is equivalent to optimizing a design with mindist.

### Value

A real number equal to the value of the \phi_p criterion for the design.

### Author(s)

G. Damblin & B.Iooss

### References

Damblin G., Couplet M., and Iooss B. (2013). Numerical studies of sapce filling designs: optimization of Latin Hypercube Samples and subprojection properties, Journal of Simulation, 7:276-289, 2013.

Fang K.-T., Li R. and Sudjianto A. (2006). Design and Modeling for Computer Experiments, Chapman & Hall.

Pronzato, L. and Muller, W. (2012). Design of computer experiments: space filling and beyond, Statistics and Computing, 22:681-701.

geometric criterion (mindist)
dimension <- 2