Man pages for HMC
High-Dimensional Mean Comparison with Projection and Cross-Fitting
| anchored_lasso_testing | Anchored test for two-sample mean comparison. |
| check_data_for_folds | Check that data has enough rows for cross-validation folds |
| check_non_null_and_identical_colnames | Check non-null and consistent column names across datasets |
| collect_active_features_proj | Collect active features and groups based on projection... |
| combine_folds_mean_diff | Combine fold-level test statistics from cross-validation |
| compute_predictive_contributions | Compute predictive contributions of feature groups |
| debiased_pc_testing | Debiased one-step test for two-sample mean comparison. A... |
| estimate_leading_pc | Estimate the leading principal component |
| estimate_nuisance_parameter_lasso | The function for nuisance parameter estimation in... |
| estimate_nuisance_pc | The function for nuisance parameter estimation in... |
| evaluate_influence_function_multi_factor | Calculate the test statistics on the left-out samples. Called... |
| evaluate_pca_lasso_plug_in | Calculate the test statistics on the left-out samples. Called... |
| evaluate_pca_plug_in | Calculate the test statistics on the left-out samples. Called... |
| extract_lasso_coef | Extract the lasso estimate from the output of... |
| extract_pc | Extract the principle components from the output of... |
| fit_lasso | Fit a (group) Lasso logistic regression classifier |
| index_spliter | Split indices into folds |
| mean_comparison_anchor | High-dimensional two-sample mean comparison with anchored... |
| normalize_and_split | Normalize and split two datasets using pooled mean and... |
| process_fold_mean_diff | Process one cross-validation fold for mean difference testing |
| simple_pc_testing | Simple plug-in test for two-sample mean comparison. |
| summarize_feature_name | Summarize the features (e.g. genes) that contribute to the... |
| summarize_pc_name | Summarize the features (e.g. genes) that contribute to the... |
| validate_and_convert_data | Validate and convert input data |
