| Type: | Package |
| Title: | Factorial Experiments with Minimum Level Changes |
| Version: | 1.0.1 |
| Maintainer: | Shwetank Lall <shwetanklall@gmail.com> |
| Description: | Generate cost effective minimally changed run sequences for symmetrical as well as asymmetrical factorial designs. |
| Imports: | minimalRSD |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| RoxygenNote: | 7.1.2 |
| NeedsCompilation: | no |
| Author: | Shwetank Lall [aut, cre], Arpan Bhowmik [ctb], Eldho Varghese [aut], Seema Jaggi [ctb], Cini Varghese [ctb] |
| Packaged: | 2022-04-17 04:42:46 UTC; JiyoSumnny |
| Repository: | CRAN |
| Date/Publication: | 2022-04-17 05:12:28 UTC |
FMC: A package for constructing minimallly changed run sequences in factorial experiments
Description
The FMC package can be used to construct run sequences with minimum changes in factor levels. Experimenter can save time and resources by minimizing the number of changes in levels of individual facor and therefore the total number of changes. The package provides the function minimal.factorial and gen.level. This technique can be employed to any symmetric or asymmetric factorial combination.
Details
In Design of Experiments (DOE) theory, levels of a factor can be represented as integers e.g. -1 for low, 0 for medium and 1 for high. This representation helps in studying factors with high number of levels. The function "gen.level()" provides the same representation for any factor with given number of total levels. User is expected to enter a vector of total number of levels for each factor to be considered in the experiment. Function "minimal.factorial()" provides the required run sequences for the input vector of level totals. The output also gives the number of changes of each factor along with total number of changes in the run sequence.
FMC functions
gen.level: Generate integers representing the levels of a factor.
minimal.factorial: Generate minimally changed runs for asymmetric
and symmetric factorial combinations..
Author(s)
Shwetank Lall shwetanklall@gmail.com
Arpan Bhowmik arpan.stat@gmail.com
Eldho Varghese eldhoiasri@gmail.com
Seema Jaggi seema@iasri.res.in
Cini Varghese cini_v@iasri.res.in
References
Arpan Bhowmik, Eldho Varghese, Seema Jaggi and Cini
Varghese(2016).Minimally changed run sequences in factorial
experiments. Communications in Statistics - Theory and Methods,
DOI: 10.1080/03610926.2016.1152490.
Arpan Bhowmik, Eldho Varghese, Seema Jaggi and Cini
Varghese (2015). Factorial Experiments with Minimum Changes
in Run Sequences. Journal of the Indian Society of
Agricultural Statistics. 69(3), 243-255.
Generate Levels
Description
Generate coded integers for given total number of levels of a factor.
Usage
gen.level(x)
Arguments
x |
An integer greater than or equal to 2. |
Value
a vector of integers as
coded levels for a factor
with total number of
levels as x.
Examples
# To generate 5 levels for a factor
gen.level(5)
Minimally Changed Run Sequences
Description
Generate minimally changed run sequences for a given asymmetrical or symmetrical factorial design.
Usage
minimal.factorial(z)
Arguments
z |
A vector of size 2 with entries integers greater than 1. |
Value
returns minimally changed run sequences for given
factorial setting as v.
Examples
#' ## make a vector of factor levels
z <- c(2,3,4)
# To generate minimmaly changed run sequence
minimal.factorial(z)
Minimally Changed BBD
Description
Generate Box Behnken design (BBD) with minimum level changes in the run sequence.
Usage
shwet(x, y)
Arguments
x |
A matrix of factor level combinations |
y |
total number of levels of new factor |
Value
returns a matrix of minimally changed run sequence