plot_obj_val_order_statistic

Plots an order statistic of the object value as a function of number of searches

Computes experimental designs for a
two-arm experiment with covariates via a number of methods:
(0) complete randomization and randomization with forced-balance,
(1) Greedily optimizing a
balance objective function via pairwise switching. This optimization
provides lower variance for the treatment effect estimator (and higher
power) while preserving a design that is close to complete randomization.
We return all iterations of the designs for use in a permutation test,
(2) The second is via numerical optimization
(via 'gurobi' which must be installed, see <https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html>)
a la Bertsimas and Kallus,
(3) rerandomization,
(4) Karp's method for one covariate,
(5) exhaustive enumeration to find the
optimal solution (only for small sample sizes),
(6) Binary pair matching using the 'nbpMatching' library,
(7) Binary pair matching plus design number (1) to further optimize balance,
(8) Binary pair matching plus design number (3) to further optimize balance,
(9) Hadamard designs,
(10) Simultaneous Multiple Kernels.
In (1-9) we allow for three objective functions:
Mahalanobis distance,
Sum of absolute differences standardized and
Kernel distances via the 'kernlab' library. This package is the result of a stream of research that can be found in
Krieger, A, Azriel, D and Kapelner, A "Nearly Random Designs with Greatly Improved Balance" (2016) <arXiv:1612.02315>,
Krieger, A, Azriel, D and Kapelner, A "Better Experimental Design by Hybridizing Binary Matching with Imbalance
Optimization" (2021) <arXiv:2012.03330>.

Adam Kapelner

GreedyExperimentalDesign

Greedy Experimental Design Construction

David Azriel

Abba Krieger

plot_obj_val_order_statistic function

<dl><dt>obj</dt>
<dd>The greedy search object object whose search history is to be visualized</dd>
<dt>order_stat</dt>
<dd>The order statistic that you wish to plot. The default is <code>1</code> for the minimum.</dd>
<dt>skip_every</dt>
<dd>Plot every nth point. This makes the plot generate much more quickly. The default is <code>5</code>.</dd>
<dt>type</dt>
<dd>The type parameter for plot.</dd>
<dt>...</dt>
<dd>Other arguments to be passed to the plot function.</dd></dl>

Arguments

Author

Plots an order statistic of the object value as a function of number of searches — plot_obj_val_order_statistic

<dl>

<dt>obj</dt>
<dd>The greedy search object object whose search history is to be visualized</dd>


<dt>order_stat</dt>
<dd>The order statistic that you wish to plot. The default is <code>1</code> for the minimum.</dd>


<dt>skip_every</dt>
<dd>Plot every nth point. This makes the plot generate much more quickly. The default is <code>5</code>.</dd>


<dt>type</dt>
<dd>The type parameter for plot.</dd>


<dt>...</dt>
<dd>Other arguments to be passed to the plot function.</dd>

</dl>

plot_obj_val_order_statistic: Plots an order statistic of the object value as a function of number of searches

Description

Usage

Value

Arguments

Author