Asymptotic Normality of Generalised Edge Frequency Polygon Estimator for Dependent Data
ABSTRACT Density function estimation is a cornerstone of statistical analysis. This paper focuses on the generalised edge frequency polygon estimator, establishing its asymptotic normality for identically distributed ‐mixing random variables. This finding complements the asymptotic theory outlined by Dong and Zheng (2001. Generalized edge frequency polygon for density estimation. Statistics and Probability Letters, 55, 137–145). Theoretical results are substantiated through simulations that assess finite‐sample performance and an analysis of a real‐world dataset.
Authors
- Aiting Shen
- Xuejun Wang
- Yan Wang
Institutions
- Anhui University (CN)
- Chizhou University (CN)
Publication Details
- Journal
- Australian & New Zealand Journal of Statistics
- Published
- 2026-02-18
- DOI
- https://doi.org/10.1111/anzs.70036
- Primary Topic
- Statistical Methods and Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00