FMC: FMC: A package for constructing minimallly changed run...
In FMC: Factorial Experiments with Minimum Level Changes
FMC R Documentation
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.
FMC documentation built on April 17, 2022, 9:05 a.m.
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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.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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