BCabootstrap
BCabootstrap is a bootstrap-based statistical method used to construct confidence intervals for a statistic by applying the bias-corrected and accelerated (BCa) adjustment. It is employed when analytic formulas for the sampling distribution are unavailable or unreliable, especially for nonparametric or skewed data.
The BCa approach starts with a primary statistic computed from the original sample. A large number of
Compared with basic percentile bootstrap intervals, BCabootstrap aims to provide more accurate coverage by compensating for
Limitations include increased computational demand due to the large number of resamples, sensitivity to outliers, and