Estimating the geographical distribution of diseasesa statistical problem

  1. Paloma Botella-Rocamora
  2. Jordi Pérez-Panadés
  3. Miguel Maríınez Beneito
Revista:
BEIO, Boletín de Estadística e Investigación Operativa

ISSN: 1889-3805

Año de publicación: 2017

Volumen: 33

Número: 1

Páginas: 4-21

Tipo: Artículo

DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: BEIO, Boletín de Estadística e Investigación Operativa

Referencias bibliográficas

  • 1] Besag, J., York, J., y Molli´e, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathemathics, 43, 1-21.
  • [2] Botella-Rocamora, P., Martinez-Beneito, M. A. y Banerjee, S. (2015). A unifying modeling framework for highly multivariate disease mapping. Statistics in Medicine, 34(9), 1548-1559.
  • [3] Knorr-Held, L. (2000). Bayesian modelling of inseparable space-time variation in disease risk. Statistics in Medicine, 19, 2555-2567.
  • [4] Dobra, A., Lenkoski, A. y Rodriguez, A. (2011). Bayesian inference for general Gaussian graphical models with application to multivariate lattice data. Journal of the American Statistical Association, 496(106), 1418-1433.
  • [5] Last, J. (2001). A dictionary of Epidemiology, Oxford University Press, New York (USA).
  • [6] Mart´ınez-Beneito, M.A., L´opez-Qu´ılez, A. y Botella-Rocamora, P. (2008). An autoregressive approach to spatio-temporal disease mapping. Statistics in Medicine, 27, 2874-2889.
  • [7] Mart´ınez-Beneito, M.A. (2013). A general modelling framework for multivariate disease mapping. Biometrika, 100(3), 539-553.
  • [8] Martinez-Beneito, M.A., Botella-Rocamora, P. y Banerjee, S. (2017). Towards a Multidimensional Approach to Bayesian Disease Mapping. Bayesian Analysis, 12(1), 239-259.
Fuente de los datos: Dialnet