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MOFAT  

Maximum One-Factor-at-a-Time Designs
View on CRAN: Click here


Download and install MOFAT package within the R console
Install from CRAN:
install.packages("MOFAT")

Install from Github:
library("remotes")
install_github("cran/MOFAT")

Install by package version:
library("remotes")
install_version("MOFAT", "1.0")



Attach the package and use:
library("MOFAT")
Maintained by
V. Roshan Joseph
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-29
Latest Update: 2022-10-29
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) 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) . 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 .
How to cite:
V. Roshan Joseph (2022). MOFAT: Maximum One-Factor-at-a-Time Designs. R package version 1.0, https://cran.r-project.org/web/packages/MOFAT. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Complete documentation for MOFAT
Functions, R codes and Examples using the MOFAT R package
Some associated functions: measure . mofat . 
Some associated R codes: mofat.R .  Full MOFAT package functions and examples
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