Strong uniform consistency of nonparametric estimation for quantile-based entropy function under length-biased sampling

Vaishnavi Pavithradas; Rajesh G

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arXiv · 2509.15734

Strong uniform consistency of nonparametric estimation for quantile-based entropy function under length-biased sampling

Vaishnavi Pavithradas·Rajesh G

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Abstract

For studies in reliability, biometry, and survival analysis, the length-biased distribution is often well-suited for certain natural sampling plans. In this paper, we study the strong uniform consistency of two nonparametric estimators for the quantile-based Shannon entropy in the context of length-biased data. A simulation study is conducted to examine the behavior of the estimators in finite samples, followed by a comparative analysis with existing estimators. Furthermore, the usefulness of the proposed estimators is evaluated using a real dataset.

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Vaishnavi Pavithradas, Rajesh G. 2025-09-19. Strong uniform consistency of nonparametric estimation for quantile-based entropy function under length-biased sampling. https://arxiv.org/abs/2509.15734

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