Answers are grounded in this paper and cite their sources.
Theoretical analysis reveals an O(n^-1/6) Berry–Esséen bound for edge frequency polygon estimators under negative dependence, suggesting convergence performance matching kernel estimators.
In this paper, we establish a Berry–Esséen bound for the edge frequency polygon estimator based on linearly extended negative quadrant-dependent (LENQD) random variables under suitable conditions. The convergence rate is shown to be On−1/6, indicating that the edge frequency polygon estimator achieves a convergence performance that is comparable to that of the kernel estimator. In addition, a simulation study is conducted to validate the theoretical findings.
No takes yet. Share an insight, caveat, or question.
Du et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: