sampleItems: Function to sample items with a genetic algorithm maximizing...

In damiencrone/gasample: A Package For Sampling Stimuli For Psychological Research Using Genetic Algorithms

Description

Function to sample items with a genetic algorithm maximizing some measure of fitness (e.g., average inter-item dissimilarity) as measured by an inter-item distance matrix.

Usage

sampleItems(distance_mat, sample_size, fitness = fitnessFunction,
  lower_tri_funciton = sumHeight, n_suggestions = 500,
  maxiter = 1e+06, run = 200, required_items = NULL, seed = NULL,
  suggest_maxmin = TRUE)

Arguments

distance_mat	a population inter-item distance matrix
sample_size	the number of items to sample
fitness	a fitness function to pass to ga()
lower_tri_funciton	the specific function to assess fitness of the lower triangle of the sample distance matrix
n_suggestions	number of suggestions to initialise the GA with
maxiter	maximum number of iterations to run GA
required_items	character vector of any items required to be included in the solution
seed	seed for GA
suggest_maxmin	logical denoting whether to include greedy search for the items that maximise minimum inter item distance in the initial suggestions

Value

a list containing the final items and a GA object

damiencrone/gasample documentation built on May 20, 2019, 9:26 a.m.