| FrF2.catlg128-package {FrF2.catlg128} | R Documentation |
Catalogues of resolution IV 128 run 2-level fractional factorials up to 33 factors that do have 5-letter words
Description
Description: This package provides the complete catalogues of those resolution IV regular fractional factorial designs in 128 runs for up to 33 2-level factors that do have length 5 words (i.e. are not even). For 8 to 11 factors, the best design (resolution higher than IV, i.e. all two-factor interactions are clear) is included only.
Details
The complete set of designs on which these catalogues are based has been provided by Xu (2009) for up to 25 factors and by Mee (2012) for 26 to 33 factors. The designs provided in this package are useful for special tasks to be accomplished with package FrF2. The catalogues are separately provided here, because they are very large and should not be forced upon FrF2 users who do not need them.
The main reason for providing the catalogues is to support estimability requirements for clear two-factor interactions in package FrF2. According to Wu, Mee and Tang (2012), resolution IV designs with no 5-letter words do not add value (there is always a better design that can accomodate the same clear two-factor interactions). Therefore, starting with version 1.1, resolution IV designs without 5-letter words have been omitted from the catalogues, and the title of the package has been changed accordingly, from the previous "Complete catalogues of resolution IV 128 run 2-level fractional factorials up to 24 factors". The previously available complete catalogues of designs can be downloaded from the author's website. Designs for 25 to 33 factors have been added with version 1.2 of the package.
Author(s)
Ulrike Groemping
Maintainer: Ulrike Groemping <ulrike.groemping@bht-berlin.de>
References
Mee, R. (2012) Personal communication. Wu, H., Mee, R. and Tang, B. (2012) Fractional Factorial Designs With Admissible Sets of Clear Two-Factor Interactions. Technometrics 54, 191-197. Xu, H. (2009) Algorithmic Construction of Efficient Fractional Factorial Designs With Large Run Sizes. Technometrics 51, 262-277.