Measuring one-dimensional diversity

Bibliographic Data

ID21335299
AuthorsKarin Enflo (0000-0001-9093-3995, Umeå University, corresponding author)
Year2026
Volume69
Issue2
Pages245-278
Publication date2026-02-07
Open AccessYes
TypeARTICLE
VenueInquiry (JOURNAL)
Journal identifiersISSN: 0020-174X • E-ISSN: 1502-3923
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/0020174x.2022.2125436
OpenAlexW4297919200
LanguageEN
References cited57

A large number of diversity measures have been proposed in the literature, almost all of which are designed for sets with elements that differ in multiple aspects. However, these types of measures are not appropriate for sets with elements that differ in a single aspect only, such as duration, value or probability. In this essay I present a new measure of diversity, designed specifically for single aspect diversity. The measure captures the intuitive idea that single aspect diversity is affected by the maximal dissimilarity between the elements, the number of different elements, and the even spacing of the elements’ aspect values, when represented as points in one dimension. I show that the measure satisfies six plausible conditions for a single aspect diversity measure, which concern scale independence, minimal diversity, maximal dissimilarity, restricted function growth, strict monotonicity, and even spacing. The measure is also characterised

Combinatorics · Data mining · Dimension (graph theory) · Diversity (politics) · Function (biology) · Independence (probability theory) · Mathematical analysis · Measure (data warehouse) · Monotonic function · Physics · Scale (ratio) · Statistics · Value (mathematics) · Agricultural Economics and Policy · Computer Science · Forest Management and Policy · Game Theory and Voting Systems · Mathematics

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