goelz_optim: Create conformity-optimized Goelz Triangle experimental...

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Creates conformity-optimized Goelz Triangle experimental designs

Usage

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goelz_optim(
  data,
  save.path = ".",
  MU = 100,
  LAMBDA = MU,
  MAX.GEN = 150,
  P.RECOMB = 1,
  RECOMB = 0.1,
  P.MUT = 1,
  MUT = 0.005
)

Arguments

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.

Details

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.

Value

An list containing:

Author(s)

Kevin J Wolz, kevin@savannainstitute.org

References

See Also

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()

Examples

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dat <- goelz_optim()

kevinwolz/sysdesign documentation built on June 13, 2020, 1:35 a.m.