MixFrac
MixFrac is an R package for constructing mixed-level and regular fractional factorial designs, with:
Automatic detection of regular designs of the form s^(k-p) Efficient mixed-level construction using a combined J2 and H^ objective NONBPA skeletons for non-multiple level structures Alias structures and confounding summary (Ríos-Lira et al.) Deterministic trend-free run orders (Coster 1993)
It is designed for practitioners needing flexible fractional factorial designs in industrial experimentation, quality engineering, and statistical design of experiments (DoE).
Installation
You can install the development version of MixFrac like so:
devtools::install("MixFrac")Example
This is a basic example which shows you how to solve a common problem: Example Usage 1. Mixed-level fractional factorial design (2 × 3 × 4), 12 runs Writing
library(MixFrac)
res <- generate_ff( c(2,3,4), # levels per factor n_runs = 12, # required runs tf = TRUE, # compute trend-free order parts = c(1,2,3), verbose = TRUE )
This produces:
Part 1: The fractional factorial design
Part 2: Metrics (H^, J2), GBM, alias chains & confounding
Part 3: Trend-free run order
- Regular 2-level fraction example (2^3 with 4 runs) Writing
res_reg <- generate_ff( c(2,2,2), 4, tf = TRUE, parts = c(1,2,3), verbose = TRUE )
The package automatically detects this as a candidate for a regular 2^(3-1) design and searches for the best generator set.
- Only print the design (Part 1) Writing
generate_ff( c(2,3,4), 12, tf = FALSE, parts = 1, verbose = TRUE )
- Only print alias structure + metrics (Parts 1 & 2) Writing
generate_ff( c(2,3,4), 12, tf = FALSE, parts = c(1,2), verbose = TRUE )
- Only trend-free ordering (Part 3) Writing
generate_ff( c(2,3,4), 12, tf = TRUE, parts = 3, verbose = TRUE )
What is special about using README.Rmd instead of just README.md?
You can include R chunks like so: Using README.Rmd allows inclusion of
executable R code, examples, and automatic generation of README.md.
Render the README with:
devtools::build_readme()
Commit:
README.md
Figures in man/figures/
for GitHub and CRAN visibility.
References
Guo, Y., Simpson, J. R., & Pignatiello, J. J. (2007). Construction of Efficient Mixed-Level Fractional Factorial Designs. Journal of Quality Technology, 39(3), 241–257. https://doi.org/10.1080/00224065.2007.11917691
Pantoja-Pacheco et al. (2021). One Note for Fractionation and Increase for Mixed-Level Designs When Levels Are Not Multiple. Mathematics, 9(13), 1455. https://doi.org/10.3390/math9131455
Ríos-Lira et al. (2021). Alias Structures and Sequential Experimentation for Mixed-Level Designs. Mathematics, 9(23), 3053. https://doi.org/10.3390/math9233053
Coster, D. C. (1993). Trend-Free Run Orders of Mixed-Level Fractional Factorial Designs. Annals of Statistics, 21(4), 2072–2086. https://doi.org/10.1214/aos/1176349410