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OptimalRerandExpDesigns (version 1.1)

Optimal Rerandomization Experimental Designs

Description

This is a tool to find the optimal rerandomization threshold in non-sequential experiments. We offer three procedures based on assumptions made on the residuals distribution: (1) normality assumed (2) excess kurtosis assumed (3) entire distribution assumed. Illustrations are included. Also included is a routine to unbiasedly estimate Frobenius norms of variance-covariance matrices. Details of the method can be found in "Optimal Rerandomization via a Criterion that Provides Insurance Against Failed Experiments" Adam Kapelner, Abba M. Krieger, Michael Sklar and David Azriel (2020) .

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install.packages('OptimalRerandExpDesigns')

Monthly Downloads

193

Version

1.1

License

GPL-3

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Maintainer

Adam Kapelner

Last Published

January 28th, 2021

Functions in OptimalRerandExpDesigns (1.1)

generate_W_base_and_sort

Generate Base Assignments and Sorts
OptimalRerandExpDesigns

Optimal Rerandomization Threshold Search for Experimental Design
complete_randomization_plus_one_min_one

Implements the complete randomization design (CRD) AKA Bernoulli Trial
complete_randomization_with_forced_balance_plus_one_min_one

Implements the balanced complete randomization design (BCRD)
frob_norm_sq

Naive Frobenius Norm Squared
optimal_rerandomization_exact

Find the Optimal Rerandomization Design Exactly
optimal_rerandomization_tail_approx

Find the Optimal Rerandomization Design Under the Tail and Kurtosis Approximation
compute_objective_val_plus_one_min_one_enc

Returns the objective value given a design vector as well an an objective function. This is code duplication since this is implemented within Java. This is only to be run if...
optimal_rerandomization_normality_assumed

Find the Optimal Rerandomization Design Under the Gaussian Approximation
frob_norm_sq_debiased

Debiased Frobenius Norm Squared Var-Cov matrix
summary.optimal_rerandomization_obj

Prints a summary of a optimal_rerandomization_obj object
summary.W_base_object

Prints a summary of a W_base_object object
print.optimal_rerandomization_obj

Prints a summary of a optimal_rerandomization_obj object
plot.W_base_object

Plots a summary of the imbalances in a W_base_object object
print.W_base_object

Prints a summary of a W_base_object object
plot.optimal_rerandomization_obj

Plots a summary of a optimal_rerandomization_obj object
frob_norm_sq_debiased_times_matrix

Debiased Frobenius Norm Squared Constant Times Var-Cov matrix