resultsGreedySearch {GreedyExperimentalDesign} | R Documentation |
Returns the results (thus far) of the greedy design search
resultsGreedySearch(obj, max_vectors = 9)
obj |
The |
max_vectors |
The number of design vectors you wish to return. |
Adam Kapelner
## Not run: library(MASS) data(Boston) #pretend the Boston data was an experiment setting #first pull out the covariates X = Boston[, 1 : 13] #begin the greedy design search ged = initGreedyExperimentalDesignObject(X, max_designs = 1000, num_cores = 2, objective = "abs_sum_diff") #wait res = resultsGreedySearch(ged, max_vectors = 2) design = res$ending_indicTs[, 1] #ordered already by best-->worst design #what is the balance on this vector? res$obj_vals[1] #compute balance explicitly in R to double check compute_objective_val(X, design) #same as above #how far have we come? ged #we can cut it here stopSearch(ged) ## End(Not run)