Browsing by Author "Gutierrez, Luis"
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- ItemMultivariate Bayesian discrimination for varietal authentication of Chilean red wine(TAYLOR & FRANCIS LTD, 2011) Gutierrez, Luis; Quintana, Fernando A.; von Baer, Dietrich; Mardones, ClaudiaThe process through which food or beverages is verified as complying with its label description is called food authentication. We propose to treat the authentication process as a classification problem. We consider multivariate observations and propose a multivariate Bayesian classifier that extends results from the univariate linear mixed model to the multivariate case. The model allows for correlation between wine samples from the same valley. We apply the proposed model to concentration measurements of nine chemical compounds named anthocyanins in 399 samples of Chilean red wines of the varieties Merlot, Carmenere and Cabernet Sauvignon, vintages 2001-2004. We find satisfactory results, with a misclassification error rate based on a leave-one-out cross-validation approach of about 4%. The multivariate extension can be generally applied to authentication of food and beverages, where it is common to have several dependent measurements per sample unit, and it would not be appropriate to treat these as independent univariate versions of a common model.
- ItemMULTIVARIATE BAYESIAN SEMIPARAMETRIC MODELS FOR AUTHENTICATION OF FOOD AND BEVERAGES(INST MATHEMATICAL STATISTICS, 2011) Gutierrez, Luis; Quintana, Fernando A.Food 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.