This function can be used for generating MOFAT designs.
Usage
mofat(p, l, method = "best")
Value
design
MOFAT design
Arguments
p
number of factors
l
number of base runs
method
choose among "uniform", "projection", and "best"
Author
Qian Xiao and V. Roshan Joseph
Details
The mofat function generates the MOFAT design
for a given number of factors (\(p\ge 2\)) and
number of base runs (\(l \ge 3\)). The total number of runs in the MOFAT design will be \(l(p+1)\).
A MOFAT design can be viewed as an optimized version of Morris screening design (Morris 1991) by exploiting
its connections with the Monte Carlo-based design of Sobol' (1993).
Please see Xiao et al. (2022) for details.
Three choices for the method are given: "uniform", "projection", and "best". Option "uniform" gives l equally-spaced levels
for the entire design, which are also balanced. "projection" option adjusts the levels of the two base matrices A and B such that
there are \(2l\) or \(2l-1\) levels in the design depending on l is even or odd. Option "best" (default) chooses the best
among the first two options using maximin distance criterion.
References
Morris, M. D. (1991), “Factorial sampling plans for preliminary computational experiments,”
Technometrics, 33, 161–174.
Sobol’, I. M. (1993), “On sensitivity estimation for nonlinear mathematical models,” Mathematical
Modeling and Computational Experiments, 1, 407–414.
Xiao, Q., Joseph, V. R., and Ray, D. M. (2022). “Maximum One-Factor-At-A-Time Designs for Screening in Computer Experiments”.
Technometrics, to appear.
#MOFAT with three base runsmofat(p=10, l=3, method="uniform")
mofat(p=10, l=3, method="projection")
#MOFAT with five base runsmofat(p=10,l=5)
dim(mofat(p=125,l=5))