Bing Yang Tan
Biographic Data
| ID | 8921104 |
|---|---|
| NAME | Bing Yang Tan |
| GIVEN NAMES | Bing Yang |
| FAMILY NAME | Tan |
| SIGNATURE | TAN B Y |
| AFFILIATIONS | Global Asia Institute, National University of Singapore, Singapore, Singapore |
| ORCID | 0000-0001-8621-5923 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Empirical Likelihood and Uniform Convergence Rates for Dyadic Kernel Density Estimation
This article studies the asymptotic properties of and alternative inference methods for kernel density estimation (KDE) for dyadic data. We first establish uniform convergence rates for dyadic KDE. Second, we propose a modified jackknife empirical likelihood procedure for inference. The proposed test statistic is asymptotically pivotal regardless of presence of dyadic clustering. The results are further extended to cover the practically relevant …
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Empirical Likelihood and Uniform Convergence Rates for Dyadic Kernel Density Estimation
This article studies the asymptotic properties of and alternative inference methods for kernel density estimation (KDE) for dyadic data. We first establish uniform convergence rates for dyadic KDE. Second, we propose a modified jackknife empirical likelihood procedure for inference. The proposed test statistic is asymptotically pivotal regardless of presence of dyadic clustering. The results are further extended to cover the practically relevant …
Artificial Intelligence (1 work) · Cluster analysis (1 work) · Computer Science (1 work) · Confidence interval (1 work) · Density estimation (1 work) · Econometrics (1 work) · Empirical likelihood (1 work) · Inference (1 work) · Jackknife resampling (1 work) · Kernel density estimation (1 work)