A nonparametric visual test of mixed hazard models

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A nonparametric visual test of mixed hazard models - RP:2399

Handle:

https://hdl.handle.net/20.500.11797/RP2399

Autor/es de la URV:	Fiig Jarner, Søren Perch Nielsen, Jens Spreeuw, Jaap
Año de publicación de la revista:	2013

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Archivo	Descripción	Formato
DocumentPrincipal	DocumentPrincipal	application/pdf

Descripción:	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.
Cobertura:	eng
Títol:	A nonparametric visual test of mixed hazard models
Materia:	mortality data, frailty models, visual inspection
Formato:	application/pdf
Autor:	Fiig Jarner, Søren Perch Nielsen, Jens Spreeuw, Jaap
Tipo:	SORT:ART info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article
Fecha:	2013
Editor:	Universitat Rovira i Virgili Universitat de Lleida Universitat de Girona Universitat Pompeu Fabra Universitat Politècnica de Catalunya Universitat Autònoma de Barcelona Universitat de Barcelona Institut d'Estadística de Catalunya

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