Linear models for statistical shape analysis based on parametrized closed curves

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dc.contributor.authorGutierrez, Luis
dc.contributor.authorMena, Ramses H.
dc.contributor.authorDiaz-Avalos, Carlos
dc.date.accessioned2025-01-23T19:51:53Z
dc.date.available2025-01-23T19:51:53Z
dc.date.issued2020
dc.description.abstractWe develop a simple, yet powerful, technique based on linear regression models of parametrized closed curves which induces a probability distribution on the planar shape space. Such parametrization is driven by control points which can be estimated from the data. Our proposal is capable to infer about the mean shape, to predict the shape of an object at an unobserved location, and, while doing so, to consider the effect of predictors on the shape. In particular, the model is able to detect possible differences across the levels of the predictor, thus also applicable for two-sample tests. A simple MCMC algorithm for Bayesian inference is also presented and tested with simulated and real datasets. Supplementary material is available online.
dc.fuente.origenWOS
dc.identifier.doi10.1007/s00362-018-0986-0
dc.identifier.eissn1613-9798
dc.identifier.issn0932-5026
dc.identifier.urihttps://doi.org/10.1007/s00362-018-0986-0
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/100605
dc.identifier.wosidWOS:000531156900014
dc.issue.numero3
dc.language.isoen
dc.pagina.final1229
dc.pagina.inicio1213
dc.revistaStatistical papers
dc.rightsacceso restringido
dc.subjectBayesian inference
dc.subjectMorphometrics
dc.subjectGeneralized procrustes analysis
dc.subjectShape regression
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleLinear models for statistical shape analysis based on parametrized closed curves
dc.typeartículo
dc.volumen61
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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