Simulation methods for squared Euclidean and Mahalanobis type distances for multivariate data and their application in assessing the uncertainty in hierarchical clustering
Author:
Affiliation:
1. Science and Technology in Archaeology and Culture Research Centre, The Cyprus Institute, Aglantzia, Cyprus
2. Department of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece
Funder
European Regional Development Fund
Research and Innovation Foundation
Horizon 2020
Publisher
Informa UK Limited
Subject
Applied Mathematics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/00949655.2022.2030338
Reference25 articles.
1. The Elements of Statistical Learning
2. Finding Groups in Data
3. Pvclust: an R package for assessing the uncertainty in hierarchical clustering
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