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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...
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| Publicado no: | J Am Stat Assoc |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Taylor & Francis
2015
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4456951/ https://ncbi.nlm.nih.gov/pubmed/26109745 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2014.908779 |
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