Description Usage Arguments Details Value Author(s) References See Also Examples
Creates conformity-optimized Goelz Triangle experimental designs
1 2 3 4 5 6 7 8 9 10 11 | goelz_optim(
data,
save.path = ".",
MU = 100,
LAMBDA = MU,
MAX.GEN = 150,
P.RECOMB = 1,
RECOMB = 0.1,
P.MUT = 1,
MUT = 0.005
)
|
data |
An object of class goelz. |
save.path |
A character string indicating the path for where to save data after each generation. |
MU |
The population size. |
LAMBDA |
The number of offspring to produce in each generation. |
MAX.GEN |
The number of generations to run the evolutionary algorithm. |
P.RECOMB |
The probability of two parents to perform crossover. |
RECOMB |
The crossover probability for each gene. |
P.MUT |
The probability to apply mutation to a child. |
MUT |
The mutation probability for each gene. |
While goelz
creates Goelz Triangle designs that roughly follow the conformity criterion set
forth by Goelz (2001), this function optimizes designs for conformity using an evolutionary algorithm. Function
parameters other than data
are all controls on the evolutionary algorithm.
The ecr
package is used for the evolutionary algorithm.
An list containing:
"layout" - A data frame (tibble) containing the base goelz design.
"stats" - A data frame (tibble) containing statistics on each generation in the evolutionary algorithm.
"data" - A data frame (tibble) containing the actual data (designs) of each Goelz Triangle in each generation.
Kevin J Wolz, kevin@savannainstitute.org
Goelz JCG (2001) Systematic experimental designs for mixed species plantings. Native Plants Journal 2:90–96. http://npj.uwpress.org/content/2/2/90.short
Other definition functions:
goelz_add_border()
,
goelz_corners()
,
goelz_guides()
,
goelz_mirror()
,
goelz_starts()
,
goelz()
,
nelder_biculture_competition()
,
nelder_biculture_optim()
,
nelder_biculture()
,
nelder_decision()
,
nelder_interspoke_distance()
,
nelder()
,
select_optimal_goelz()
,
select_optimal_nelder_biculture()
1 | dat <- goelz_optim()
|
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