View source: R/binary_match_followed_by_rerandomization_search.R
| resultsBinaryMatchThenRerandomizationSearch | R Documentation |
Returns unique allocation vectors that are binary matched
resultsBinaryMatchThenRerandomizationSearch(
obj,
num_vectors = NULL,
compute_obj_vals = FALSE,
form = "one_zero",
use_safe_inverse = FALSE
)
obj |
The |
num_vectors |
How many random allocation vectors you wish to return. The default is |
compute_obj_vals |
Should we compute all the objective values for each allocation? Default is |
form |
Which form should it be in? The default is |
use_safe_inverse |
Should a regularized inverse be used for the Mahalanobis objective?
Default is |
Adam Kapelner
## Not run:
set.seed(1)
X = matrix(rnorm(16), nrow = 8)
obj = initBinaryMatchFollowedByRerandomizationDesignSearchObject(
X,
max_designs = 4,
num_cores = 1,
objective = "abs_sum_diff",
obj_val_cutoff_to_include = Inf,
start = TRUE,
wait = TRUE,
verbose = FALSE
)
res = resultsBinaryMatchThenRerandomizationSearch(obj, num_vectors = 3, form = "one_zero")
dim(res$indicTs)
## End(Not run)
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