extract_pc

Extract the principle components from the output of simple_pc_testing() and debiased_pc_testing().

Provides interpretable High-dimensional Mean Comparison methods (HMC). For example, users can use them to assess the difference in gene expression between two treatment groups. It is not a gene-by-gene comparison. Instead, we focus on the interplay between features and are interested in those that are predictive of the group label. The methods are valid frequentist tests and give sparse estimates indicating which features contribute to the test results.

Tianyu Zhang

High Dimensional Mean Comparison with Projection and
Cross-Fitting

extract_pc function

<dl><dt>testing_result</dt>
<dd>The output/test result list from simple_pc_testing() or debiased_pc_testing().</dd></dl>

Arguments

Extract the principle components from the output of simple_pc_testing() and debiased_pc_testing(). — extract_pc

<dl>

<dt>testing_result</dt>
<dd>The output/test result list from simple_pc_testing() or debiased_pc_testing().</dd>

</dl>

extract_pc: Extract the principle components from the output of simple_pc_testing() and debiased_pc_testing().

Description

Usage

Value

Arguments