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.

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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
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article

Asymptotic Normality of Generalised Edge Frequency Polygon Estimator for Dependent Data

Aiting Shen, Xuejun Wang, Yan Wang
Australian & New Zealand Journal of Statistics
Statistical Methods and Inference
article

Asymptotic Normality of Generalised Edge Frequency Polygon Estimator for Dependent Data

Aiting Shen, Xuejun Wang, Yan Wang
article en

Abstract

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.

Australian & New Zealand Journal of StatisticsVol. 68(1)
Anhui University (CN), Chizhou University (CN)
Openalex Percentile: Top 54%
Statistical Methods and Inference
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