MULTIVARIATE BAYESIAN SEMIPARAMETRIC MODELS FOR AUTHENTICATION OF FOOD AND BEVERAGES

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dc.contributor.authorGutierrez, Luis
dc.contributor.authorQuintana, Fernando A.
dc.date.accessioned2024-01-10T12:40:43Z
dc.date.available2024-01-10T12:40:43Z
dc.date.issued2011
dc.description.abstractFood and beverage authentication is the process by which foods or beverages are verified as complying with its label description, for example, verifying if the denomination of origin of an olive oil bottle is correct or if the variety of a certain bottle of wine matches its label description. The common way to deal with an authentication process is to measure a number of attributes on samples of food and then use these as input for a classification problem. Our motivation stems from data consisting of measurements of nine chemical compounds denominated Anthocyanins, obtained from samples of Chilean red wines of grape varieties Cabernet Sauvignon, Merlot and Carmenere. We consider a model-based approach to authentication through a semiparametric multivariate hierarchical linear mixed model for the mean responses, and covariance matrices that are specific to the classification categories. Specifically, we propose a model of the ANOVA-DDP type, which takes advantage of the fact that the available covariates are discrete in nature. The results suggest that the model performs well compared to other parametric alternatives. This is also corroborated by application to simulated data.
dc.description.funderFONDEF
dc.description.funderComision Nacional de Investigacion Cientifica y Tecnologica-CONICYT
dc.fechaingreso.objetodigital2024-05-15
dc.format.extent18 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1214/11-AOAS492
dc.identifier.issn1932-6157
dc.identifier.urihttps://doi.org/10.1214/11-AOAS492
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/77341
dc.identifier.wosidWOS:000300382800007
dc.information.autorucMatemática;Quintana F;S/I;100343
dc.issue.numero4
dc.language.isoen
dc.nota.accesocontenido completo
dc.pagina.final2402
dc.pagina.inicio2385
dc.publisherINST MATHEMATICAL STATISTICS
dc.revistaANNALS OF APPLIED STATISTICS
dc.rightsacceso abierto
dc.subjectClassification
dc.subjectdependent Dirichlet process
dc.subjectwines
dc.subjectCLASSIFICATION
dc.subjectANTHOCYANINS
dc.subjectCULTIVARS
dc.subjectWINES
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleMULTIVARIATE BAYESIAN SEMIPARAMETRIC MODELS FOR AUTHENTICATION OF FOOD AND BEVERAGES
dc.typeartículo
dc.volumen5
sipa.codpersvinculados100343
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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