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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "distanceHD" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'distanceHD: Distance Metrics for High-Dimensional Clustering'
version: '1.2'
doi: 10.32614/CRAN.package.distanceHD
abstract: We provide three distance metrics for measuring the separation between two
  clusters in high-dimensional spaces. The first metric is the centroid distance,
  which calculates the Euclidean distance between the centers of the two groups. The
  second is a ridge Mahalanobis distance, which incorporates a ridge correction constant,
  alpha, to ensure that the covariance matrix is invertible. The third metric is the
  maximal data piling distance, which computes the orthogonal distance between the
  affine spaces spanned by each class. These three distances are asymptotically interconnected
  and are applicable in tasks such as discrimination, clustering, and outlier detection
  in high-dimensional settings.
authors:
- family-names: Lee
  given-names: Jung Ae
  email: jungaeleeb@gmail.com
- family-names: Ahn
  given-names: Jeongyoun
  email: jyahn@kaist.ac.kr
repository: https://jungaeleeb.r-universe.dev
commit: b910956ce7b276c282e14062f18babff84d3c1b5
date-released: '2025-01-31'
contact:
- family-names: Lee
  given-names: Jung Ae
  email: jungaeleeb@gmail.com