A wild block bootstrap max-test detects significant predictors in high-dimensional dependent data by approximating the distribution of the maximum marginal regression coefficient without covariance estimation or post-selection adjustments.
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A High Dimensional Wild Bootstrap Max-Test for Detecting the Presence of Significant Predictors
A wild block bootstrap max-test detects significant predictors in high-dimensional dependent data by approximating the distribution of the maximum marginal regression coefficient without covariance estimation or post-selection adjustments.