Classification of form under heterogeneity and non-isotropic errors

DOI10.1080/02664763.2016.1214246OpenAlexW2479393976WikidataQ59888555 ScholiaQ59888555MaRDI QIDQ5138644

Charles C. Taylor, Arief Gusnanto, Farag Shuweihdi

Publication date: 4 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: http://eprints.whiterose.ac.uk/111230/1/Classification%20of%20Form%20%28second%20revised%20%20%29.pdf

zbMATH Keywords

classificationdistancesimilaritydata miningshape analysis

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• A solution to the weighted Procrustes problem in which the transformation is in agreement with the loss function
• The statistical theory of shape
• Assessing landmark influence on shape variation
• Euclidean distance matrix analysis (EDMA): Estimation of mean form and mean form difference
• The elements of statistical learning. Data mining, inference, and prediction
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