arXiv 4 Apr 2025 · Statistics — Methodology
arXiv:2504.03594 · PDF · DOI · OpenAlex · Extracted main text
Critical bandwidth (CB) is used to test the multimodality of densities and regression functions, as well as for clustering methods. CB tests are known to be inconsistent if the function of interest is constant ("flat") over even a small interval, and to suffer from low power and incorrect size in finite samples if the function has a relatively small derivative over an interval. This paper proposes a solution, flatness-robust CB (FRCB), that exploits the novel observation that the inconsistency manifests only from regions consistent with the null hypothesis, and thus identifying and excluding them does not alter the null or alternative sets. I provide sufficient conditions for consistency of FRCB, and simulations of a test of regression monotonicity demonstrate the finite-sample properties of FRCB compared with CB for various regression functions. Surprisingly, FRCB performs better than CB in some cases where there are no flat regions, which can be explained by FRCB essentially giving more importance to parts of the function where there are larger violations of the null hypothesis. I illustrate the usefulness of FRCB with an empirical analysis of the monotonicity of the conditional mean function of radiocarbon age with respect to calendar age.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Bowman, AW, Jones, MC, Gijbels, Irène (1998) Testing Monotonicity of Regression | 0.941 | 6 | 3 | 83% |
| 2 | Kostyshak, Scott (2017) Non-Parametric Testing of U-Shaped Relationships self | 0.928 | 5 | 4 | 80% |
| 3 | Silverman, Bernard W (1983) Some Properties of a Test for Multimodality Based on Kernel Density Estimates | 0.737 | 3 | 2 | 100% |
| 4 | Hall, Peter, Heckman, Nancy E (2000) Testing for Monotonicity of a Regression Mean by Calibrating for Linear Functions | 0.644 | 3 | 2 | 67% |
| 5 | Harezlak, Jaroslaw, Heckman, Nancy E (2001) CriSP: A Tool for Bump Hunting | 0.644 | 2 | 2 | 100% |
| 6 | Silverman, Bernard W (1981) Using Kernel Density Estimates to Investigate Multimodality | 0.644 | 2 | 2 | 100% |
| 7 | Cheng, M-Y, Hall, Peter (1998) Calibrating the Excess Mass and Dip Tests of Modality | 0.511 | 2 | 1 | 100% |
| 8 | Ameijeiras-Alonso, Jose, Crujeiras, Rosa M, Rodríguez-Casal, Alberto (2019) Mode Testing, Critical Bandwidth and Excess Mass | 0.405 | 1 | 1 | 100% |
| 9 | Belloni, Alexandre, Chernozhukov, Victor, Chetverikov, Denis, Kato,… (2015) Some New Asymptotic Theory for Least Squares Series: Pointwise and Uniform Results | 0.405 | 1 | 1 | 100% |
| 10 | Chen, Xiaohong, Christensen, Timothy M (2018) Optimal Sup-norm Rates and Uniform Inference on Nonlinear Functionals of Nonparametric IV Regression | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 28 scored citations.