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: 2026-10-16 07:38:24 UTC; root
Author: Qian Xiao [aut], V. Roshan Joseph [aut, cre]
Maintainer: V. Roshan Joseph <roshan@gatech.edu>
Repository: https://vroshanjoseph.r-universe.dev
Date/Publication: 2022-10-29 07:52:56 UTC
RemoteUrl: https://github.com/cran/MOFAT
RemoteRef: HEAD
RemoteSha: c608e1edcc80ec0afb47fd9c7b731e836e9ddcd4