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Autori principali: Wei, Yashi, Hu, Jiang, Bai, Zhidong
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2511.01603
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author Wei, Yashi
Hu, Jiang
Bai, Zhidong
author_facet Wei, Yashi
Hu, Jiang
Bai, Zhidong
contents A large class of statistics can be formulated as smooth functions of sample means of random vectors. In this paper, we propose a general partial Cramér's condition (GPCC) and apply it to establish the validity of the Edgeworth expansion for the distribution function of these functions of sample means. Additionally, we apply the proposed theorems to several specific statistics. In particular, by verifying the GPCC, we demonstrate for the first time the validity of the formal Edgeworth expansion of Pearson's correlation coefficient between random variables with absolutely continuous and discrete components. Furthermore, we conduct a series of simulation studies that show the Edgeworth expansion has higher accuracy.
format Preprint
id arxiv_https___arxiv_org_abs_2511_01603
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A general partial Cramér's condition for Edgeworth expansion of a function of sample means with applications
Wei, Yashi
Hu, Jiang
Bai, Zhidong
Probability
A large class of statistics can be formulated as smooth functions of sample means of random vectors. In this paper, we propose a general partial Cramér's condition (GPCC) and apply it to establish the validity of the Edgeworth expansion for the distribution function of these functions of sample means. Additionally, we apply the proposed theorems to several specific statistics. In particular, by verifying the GPCC, we demonstrate for the first time the validity of the formal Edgeworth expansion of Pearson's correlation coefficient between random variables with absolutely continuous and discrete components. Furthermore, we conduct a series of simulation studies that show the Edgeworth expansion has higher accuracy.
title A general partial Cramér's condition for Edgeworth expansion of a function of sample means with applications
topic Probability
url https://arxiv.org/abs/2511.01603