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

A nonparametric visual test of mixed hazard models

  • Datos identificativos

    Identificador: RP:2399
    Autores:
    Fiig Jarner, SørenPerch Nielsen, JensSpreeuw, Jaap
    Resumen:
    We consider mixed hazard models and introduce a new visual inspection technique capable of detecting the credibility of our model assumptions. Our technique is based on a transformed data approach, where the density of the transformed data should be close to the uniform distribution when our model assumptions are correct. To estimate the density on the transformed axis we take advantage of a recently defined local linear density estimator based on filtered data. We apply the method to national mortality data and show that it is capable of detecting signs of heterogeneity even in small data sets with substantial variability in observed death rates.
  • Otros:

    Autor/es de la URV: Fiig Jarner, Søren Perch Nielsen, Jens Spreeuw, Jaap
    Palabras clave: mortality data, frailty models, visual inspection
    Resumen: We consider mixed hazard models and introduce a new visual inspection technique capable of detecting the credibility of our model assumptions. Our technique is based on a transformed data approach, where the density of the transformed data should be close to the uniform distribution when our model assumptions are correct. To estimate the density on the transformed axis we take advantage of a recently defined local linear density estimator based on filtered data. We apply the method to national mortality data and show that it is capable of detecting signs of heterogeneity even in small data sets with substantial variability in observed death rates.
    Año de publicación de la revista: 2013
    Tipo de publicación: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article
  • Palabras clave:

    mortality data, frailty models, visual inspection
  • Documentos:

  • Cerca a google

    Search to google scholar