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Bibliographic Details
Main Author: Zhang, Qingyang
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2401.05281
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author Zhang, Qingyang
author_facet Zhang, Qingyang
contents We introduce a new type of influence function, the asymptotic expected sensitivity function, which is often equivalent to but mathematically more tractable than the traditional one based on the Gateaux derivative. To illustrate, we study the robustness of some important rank correlations, including Spearman's and Kendall's correlations, and the recently developed Chatterjee's correlation.
format Preprint
id arxiv_https___arxiv_org_abs_2401_05281
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Asymptotic expected sensitivity function and its applications to nonparametric correlation estimators
Zhang, Qingyang
Methodology
We introduce a new type of influence function, the asymptotic expected sensitivity function, which is often equivalent to but mathematically more tractable than the traditional one based on the Gateaux derivative. To illustrate, we study the robustness of some important rank correlations, including Spearman's and Kendall's correlations, and the recently developed Chatterjee's correlation.
title Asymptotic expected sensitivity function and its applications to nonparametric correlation estimators
topic Methodology
url https://arxiv.org/abs/2401.05281