Revistes Publicacions URV: SORT - Statistics and Operations Research Transactions> 2013

Quantile estimation of the rejection distribution of food products integrating assessor values and interval-censored consumer data

  • Datos identificativos

    Identificador: RP:2400
    Handle: https://hdl.handle.net/20.500.11797/RP2400
    Autores:
    Hough, GuillermoGómez, GuadalupeLangohr, Klaus
    Resumen:
    Fitting parametric survival models with interval-censored data is a common task in survival analysis and implemented in many statistical software packages. Here, we present a novel approach to fit such models if the values on the scale of interest are measured with error. Random effects ANOVA models are used to account for the measurement errors and the likelihood function of the parametric survival model is maximized with numerical methods. An illustration is provided with a real data set on the rejection of yogurt as a function of its acid taste

  • Otros:

    Autor/es de la URV: Hough, Guillermo Gómez, Guadalupe Langohr, Klaus
    Palabras clave: interval-censored data, maximization of the likelihood function, parametric survival model, sensory shelf-life data
    Resumen: Fitting parametric survival models with interval-censored data is a common task in survival analysis and implemented in many statistical software packages. Here, we present a novel approach to fit such models if the values on the scale of interest are measured with error. Random effects ANOVA models are used to account for the measurement errors and the likelihood function of the parametric survival model is maximized with numerical methods. An illustration is provided with a real data set on the rejection of yogurt as a function of its acid taste
    Año de publicación de la revista: 2013
    Tipo de publicación: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article

  • Palabras clave:

    interval-censored data, maximization of the likelihood function, parametric survival model, sensory shelf-life data

  • Documentos:

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