evaluate_pca_lasso_plug_in: Calculate the test statistics on the left-out samples. Called...

In HMC: High-Dimensional Mean Comparison with Projection and Cross-Fitting

Calculate the test statistics on the left-out samples. Called in anchored_lasso_testing().

Description

Calculate the test statistics on the left-out samples. Called in anchored_lasso_testing().

Usage

evaluate_pca_lasso_plug_in(
  cross_fitting_sample_1,
  cross_fitting_sample_2,
  nuisance_collection,
  mean_method = "lasso"
)

Arguments

cross_fitting_sample_1	Group 1 sample. Each row is a subject and each column corresponds to a feature.
cross_fitting_sample_2	Group 2 sample. Each row is a subject and each column corresponds to a feature.
nuisance_collection	A collection of nuisance quantities estimated using "nuisance" samples. It is the output of estimate_nuisance_pc().
mean_method	Methods used to estimate the discriminant direction. Default is logistic Lasso "lasso". Can also take value "lasso_no_truncation"

Value

A list of test statistics.

influence_each_subject_1	Test statistics for sample 1.
influence_each_subject_1	Test statistics for sample 2.
for_variance_each_subject_1	Statistics for variance calculation, sample 1.
for_variance_each_subject_2	Statistics for variance calculation, sample 2.

HMC documentation built on June 8, 2025, 10:32 a.m.