IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v51y2006i2p1347-1363.html
   My bibliography  Save this article

Hierarchical Bayesian modelling of spatial age-dependent mortality

Author

Listed:
  • Miklos Arato, N.
  • Dryden, Ian L.
  • Taylor, Charles C.

Abstract

No abstract is available for this item.

Suggested Citation

  • Miklos Arato, N. & Dryden, Ian L. & Taylor, Charles C., 2006. "Hierarchical Bayesian modelling of spatial age-dependent mortality," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1347-1363, November.
    • Handle: RePEc:eee:csdana:v:51:y:2006:i:2:p:1347-1363
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(06)00042-9
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Håvard Rue, 2001. "Fast sampling of Gaussian Markov random fields," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 325-338.
    2. Petros Dellaportas & Adrian F. M. Smith & Photis Stavropoulos, 2001. "Bayesian analysis of mortality data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 275-291.
    3. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    4. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    5. Kim H. & Sun D. & Tsutakawa R.K., 2001. "A Bivariate Bayes Method for Improving the Estimates of Mortality Rates With a Twofold Conditional Autoregressive Model," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1506-1521, December.
    6. Roger J. Marshall, 1991. "Mapping Disease and Mortality Rates Using Empirical Bayes Estimators," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(2), pages 283-294, June.
    7. Volker Schmid & Leonhard Held, 2004. "Bayesian Extrapolation of Space–Time Trends in Cancer Registry Data," Biometrics, The International Biometric Society, vol. 60(4), pages 1034-1042, December.
    8. Leonhard Knorr‐Held & Håvard Rue, 2002. "On Block Updating in Markov Random Field Models for Disease Mapping," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(4), pages 597-614, December.
    9. Green P.J. & Richardson S., 2002. "Hidden Markov Models and Disease Mapping," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1055-1070, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Volker Schmid & Leonhard Held, 2004. "Bayesian Extrapolation of Space–Time Trends in Cancer Registry Data," Biometrics, The International Biometric Society, vol. 60(4), pages 1034-1042, December.
    2. Leonhard Knorr-Held & Günter Raßer & Nikolaus Becker, 2002. "Disease Mapping of Stage-Specific Cancer Incidence Data," Biometrics, The International Biometric Society, vol. 58(3), pages 492-501, September.
    3. Brezger, Andreas & Lang, Stefan, 2006. "Generalized structured additive regression based on Bayesian P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 967-991, February.
    4. repec:jss:jstsof:21:i08 is not listed on IDEAS
    5. Douglas R. M. Azevedo & Marcos O. Prates & Dipankar Bandyopadhyay, 2021. "MSPOCK: Alleviating Spatial Confounding in Multivariate Disease Mapping Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 464-491, September.
    6. Samson B. Adebayo, 2004. "Bayesian geoadditive modelling of breastfeeding initiation in Nigeria," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 267-281.
    7. Håvard Rue & Ingelin Steinsland & Sveinung Erland, 2004. "Approximating hidden Gaussian Markov random fields," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 877-892, November.
    8. Gamerman, Dani & Moreira, Ajax R. B. & Rue, Havard, 2003. "Space-varying regression models: specifications and simulation," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 513-533, March.
    9. Vinicius Mayrink & Dani Gamerman, 2009. "On computational aspects of Bayesian spatial models: influence of the neighboring structure in the efficiency of MCMC algorithms," Computational Statistics, Springer, vol. 24(4), pages 641-669, December.
    10. I. Gede Nyoman M. Jaya & Henk Folmer, 2021. "Bayesian spatiotemporal forecasting and mapping of COVID‐19 risk with application to West Java Province, Indonesia," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 849-881, September.
    11. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    12. Stefan Lang & Samson B. Adebayo & Ludwig Fahrmeir & Winfried J. Steiner, 2003. "Bayesian Geoadditive Seemingly Unrelated Regression," Computational Statistics, Springer, vol. 18(2), pages 263-292, July.
    13. Eibich, Peter & Ziebarth, Nicolas, 2014. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
    14. McCausland, William J. & Miller, Shirley & Pelletier, Denis, 2011. "Simulation smoothing for state-space models: A computational efficiency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 199-212, January.
    15. Mayer Alvo & Jingrui Mu, 2023. "COVID-19 Data Analysis Using Bayesian Models and Nonparametric Geostatistical Models," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
    16. Louise Choo & Stephen G. Walker, 2008. "A new approach to investigating spatial variations of disease," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 395-405, April.
    17. Dolores Catelan & Annibale Biggeri & Corrado Lagazio, 2009. "On the clustering term in ecological analysis: how do different prior specifications affect results?," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(1), pages 49-61, March.
    18. Massimo Bilancia & Giacomo Demarinis, 2014. "Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA)," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 71-94, March.
    19. Ephraim M. Hanks, 2017. "Modeling Spatial Covariance Using the Limiting Distribution of Spatio-Temporal Random Walks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 497-507, April.
    20. Ying C. MacNab, 2018. "Some recent work on multivariate Gaussian Markov random fields," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 497-541, September.
    21. Francisca Corpas-Burgos & Miguel A. Martinez-Beneito, 2021. "An Autoregressive Disease Mapping Model for Spatio-Temporal Forecasting," Mathematics, MDPI, vol. 9(4), pages 1-17, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:51:y:2006:i:2:p:1347-1363. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.