R: Finds matching using heuristic based on linear discriminant...
search_heuristic1
R Documentation
Finds matching using heuristic based on linear discriminant analysis.
Description
At each vertex of the search graph, this takes a step which moves the
proportions of conditions in the subspace closer to the desired (or sample)
proportions, so the expected proportions are enforced.
A columnwise matrix containing
covariates to match the conditions on.
halting_test
A function to apply to 'covariates' (in matrix form)
which is TRUE iff the conditions are matched.
Signature: halting_test(condition, covariates, thresh).
The following halting tests are part of this package:
t_halt, U_halt,
l_halt, ad_halt,
ks_halt, wilks_halt,
f_halt.
You can create the intersection of two or more halting
tests using create_halting_test.
thresh
The return value of halting_test has to be greater than
or equal to thresh for the matched groups.
props
Either the desired proportions (percentage) of the
sample for each condition as a named vector,
or the names of the conditions
for which we prefer to preserve the subjects,
in decreasing order of preference. If not specified, the
(full) sample proportions are used.
This is enforced by the "heuristic1" method,
preferred among configurations with the same number of
total subjects by the "exhaustive" method, and
taken into account by the other methods to some extent.
For example, c(A = 0.4, B = 0.4, C = 0.2) means that
we would like the number of subjects in groups A, B, and
C to be around 40%, 40%, and 20% of the total number of
subjects, respectively. Whereas c("A", "B", "C") means
that if possible, we would like to keep all subjects
in group A, and prefer keeping subjects in B, even if
it results in losing more subjects from C.
max_removed
The maximum number of subjects that can be removed from
each group. It must have a valid number for each group.
print_info
If TRUE, prints summary information on the input and the
results, as well as progress information for the
exhaustive search and random algorithms. Default: TRUE;
can be changed using
set_param("PRINT_INFO", FALSE).
...
Consumes extra parameters that are not used by the
search algorithm at hand; this function gives a warning
about the ones whose value is not NULL that their value
is not used.
Value
All results found by search method in a list. It raises a
"Convergence failure" error if it cannot find a matched set.