computeBinaryMatchStructure {GreedyExperimentalDesign} | R Documentation |
Compute Binary Matching Strcuture
Description
This method creates an object of type binary_match_structure and will compute pairs. You can then
use the functions initBinaryMatchExperimentalDesignSearch
and resultsBinaryMatchSearch
to create randomized allocation vectors. For one column in X, we just sort to find the pairs trivially.
Usage
computeBinaryMatchStructure(
X,
mahal_match = FALSE,
compute_dist_matrix = NULL,
D = NULL
)
Arguments
X |
The design matrix with $n$ rows (one for each subject) and $p$ columns (one for each measurement on the subject). This is the design matrix you wish to search for a more optimal design. |
mahal_match |
Match using Mahalanobis distance. Default is |
compute_dist_matrix |
The function that computes the distance matrix between every two observations in |
D |
A distance matrix precomputed. The default is |
Value
An object of type binary_experimental_design
which can be further operated upon.
Author(s)
Adam Kapelner