Package: MOFAT
Title: Maximum One-Factor-at-a-Time Designs
Version: 1.0
Authors@R: c(
    person(given = "Qian",
           family = "Xiao",
           role = c("aut"),
           email = "QIAN.XIAO@uga.edu"),
    person(given = "V. Roshan",
           family = "Joseph",
           role = c("aut", "cre"),
           email = "roshan@gatech.edu"))
Imports: SLHD, stats
Description: Identifying important factors from a large number of potentially important factors of a highly nonlinear and computationally expensive black box model is a difficult problem. Xiao, Joseph, and Ray (2022) <doi:10.1080/00401706.2022.2141897> proposed Maximum One-Factor-at-a-Time (MOFAT) designs for doing this. A MOFAT design can be viewed as an improvement to the random one-factor-at-a-time (OFAT) design proposed by Morris (1991) <doi:10.1080/00401706.1991.10484804>. The improvement is achieved by exploiting the connection between Morris screening designs and Monte Carlo-based Sobol' designs, and optimizing the design using a space-filling criterion. This work is supported by a U.S. National Science Foundation (NSF) grant CMMI-1921646 <https://www.nsf.gov/awardsearch/showAward?AWD_ID=1921646>.
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.2.1
NeedsCompilation: no
Packaged: 2022-10-27 21:16:53 UTC; rv48
Author: Qian Xiao [aut],
  V. Roshan Joseph [aut, cre]
Maintainer: V. Roshan Joseph <roshan@gatech.edu>
Repository: CRAN
Date/Publication: 2022-10-29 08:52:56 UTC
Built: R 4.6.0; ; 2026-04-26 01:17:38 UTC; unix
