MOFAT
Maximum One-Factor-at-a-Time Designs
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling linux/jammy R-4.5 | MOFAT_1.0.tar.gz |
19.8 KiB |
1.0 |
rolling linux/noble R-4.5 | MOFAT_1.0.tar.gz |
19.7 KiB |
1.0 |
rolling source/ R- | MOFAT_1.0.tar.gz |
4.2 KiB |
1.0 |
latest linux/jammy R-4.5 | MOFAT_1.0.tar.gz |
19.8 KiB |
1.0 |
latest linux/noble R-4.5 | MOFAT_1.0.tar.gz |
19.7 KiB |
1.0 |
latest source/ R- | MOFAT_1.0.tar.gz |
4.2 KiB |
1.0 |
2026-04-26 source/ R- | MOFAT_1.0.tar.gz |
4.2 KiB |
1.0 |
2026-04-23 source/ R- | MOFAT_1.0.tar.gz |
4.2 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | MOFAT_1.0.zip |
22.2 KiB |
1.0 |
2025-04-20 source/ R- | MOFAT_1.0.tar.gz |
4.2 KiB |