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Size and Shape Analysis of Error-Prone Shape Data
We consider the problem of comparing sizes and shapes of objects when landmark data are prone to measurement error. We show that naive implementation of ordinary Procrustes analysis that ignores measurement error can compromise inference. To account for measurement error, we propose the conditional...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4456951/ https://www.ncbi.nlm.nih.gov/pubmed/26109745 http://dx.doi.org/10.1080/01621459.2014.908779 |