Layman’s abstract for ASMBI paper: Interpoint distances: Applications, properties, and visualization of interpoint distances

Every few days, we will be publishing layman’s abstracts of new articles from our prestigious portfolio of journals in statistics. The aim is to highlight the latest research to a broader audience in an accessible format.

The article featured today is from Applied Stochastic Models in Business and Industry, with the full article now available to read on Early View here.

Modarres, R, Song, Y. Interpoint distances: Applications, properties, and visualization. Appl Stochastic Models Bus Ind. 2020; 1– 22. doi: 10.1002/asmb.2508

This article surveys recent development of the Euclidean interpoint distances. Interpoint distances are widely used in many scientific fields, including machine learning, data mining, homogeneity testing of distributions, classifications, clustering and multidimensional scaling. The article discusses the properties and applications of Euclidean interpoint distances for several multivariate distribution families. The article also develops a method for simultaneous display of the distribution of the interpoint distances to visualize and examine the homogeneity of multivariate observations.


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