The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

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

  1. 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.

  1. Only print the design (Part 1) Writing

generate_ff( c(2,3,4), 12, tf = FALSE, parts = 1, verbose = TRUE )

  1. Only print alias structure + metrics (Parts 1 & 2) Writing

generate_ff( c(2,3,4), 12, tf = FALSE, parts = c(1,2), verbose = TRUE )

  1. 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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.