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Bibliographic Details
Main Author: Zhang, Qingyang
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.06813
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author Zhang, Qingyang
author_facet Zhang, Qingyang
contents This study investigates the extension of distance variance, a validated spread metric for continuous and binary variables [Edelmann et al., 2020, Ann. Stat., 48(6)], to quantify the spread of general categorical variables. We provide both geometric and algebraic characterizations of distance variance, revealing its connections to some commonly used entropy measures, and the variance-covariance matrix of the one-hot encoded representation. However, we demonstrate that distance variance fails to satisfy the Schur-concavity axiom for categorical variables with more than two categories, leading to counterintuitive results. This limitation hinders its applicability as a universal measure of spread.
format Preprint
id arxiv_https___arxiv_org_abs_2405_06813
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A note on distance variance for categorical variables
Zhang, Qingyang
Methodology
Statistics Theory
This study investigates the extension of distance variance, a validated spread metric for continuous and binary variables [Edelmann et al., 2020, Ann. Stat., 48(6)], to quantify the spread of general categorical variables. We provide both geometric and algebraic characterizations of distance variance, revealing its connections to some commonly used entropy measures, and the variance-covariance matrix of the one-hot encoded representation. However, we demonstrate that distance variance fails to satisfy the Schur-concavity axiom for categorical variables with more than two categories, leading to counterintuitive results. This limitation hinders its applicability as a universal measure of spread.
title A note on distance variance for categorical variables
topic Methodology
Statistics Theory
url https://arxiv.org/abs/2405.06813