IDEAS home Printed from https://ideas.repec.org/r/bla/biomet/v61y2005i4p950-961.html
   My bibliography  Save this item

Generalized Hierarchical Multivariate CAR Models for Areal Data

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Mahmoud Torabi, 2014. "Hierarchical Bayesian bivariate disease mapping: analysis of children and adults asthma visits to hospital," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 612-621, March.
  2. Colette Mair & Sema Nickbakhsh & Richard Reeve & Jim McMenamin & Arlene Reynolds & Rory N Gunson & Pablo R Murcia & Louise Matthews, 2019. "Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-21, December.
  3. Marco Gramatica & Peter Congdon & Silvia Liverani, 2021. "Bayesian modelling for spatially misaligned health areal data: A multiple membership approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 645-666, June.
  4. Marcos O. Prates & Douglas R. M. Azevedo & Ying C. MacNab & Michael R. Willig, 2022. "Non‐separable spatio‐temporal models via transformed multivariate Gaussian Markov random fields," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1116-1136, November.
  5. Wall, Melanie M. & Liu, Xuan, 2009. "Spatial latent class analysis model for spatially distributed multivariate binary data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3057-3069, June.
  6. MacNab, Ying C. & Lin, Yi, 2009. "On empirical Bayes penalized quasi-likelihood inference in GLMMs and in Bayesian disease mapping and ecological modeling," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2950-2967, June.
  7. Yin Song & Shufei Ge & Jiguo Cao & Liangliang Wang & Farouk S. Nathoo, 2022. "A Bayesian spatial model for imaging genetics," Biometrics, The International Biometric Society, vol. 78(2), pages 742-753, June.
  8. Deb, Soudeep & Karmakar, Sayar, 2023. "A novel spatio-temporal clustering algorithm with applications on COVID-19 data from the United States," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
  9. 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.
  10. Berloco, Claudia & Argiento, Raffaele & Montagna, Silvia, 2023. "Forecasting short-term defaults of firms in a commercial network via Bayesian spatial and spatio-temporal methods," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1065-1077.
  11. Cindy Xin Feng, 2015. "Bayesian joint modeling of correlated counts data with application to adverse birth outcomes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(6), pages 1206-1222, June.
  12. Nicole H. Augustin & Stefan Lang & Monica Musio & Klaus Von Wilpert, 2007. "A spatial model for the needle losses of pine‐trees in the forests of Baden‐Württemberg: an application of Bayesian structured additive regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(1), pages 29-50, January.
  13. Lopes, Hedibert Freitas & Gamerman, Dani & Salazar, Esther, 2011. "Generalized spatial dynamic factor models," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1319-1330, March.
  14. Takahiro Yoshida & Morito Tsutsumi, 2018. "On the effects of spatial relationships in spatial compositional multivariate models," Letters in Spatial and Resource Sciences, Springer, vol. 11(1), pages 57-70, March.
  15. Wang, Craig & Furrer, Reinhard, 2021. "Combining heterogeneous spatial datasets with process-based spatial fusion models: A unifying framework," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
  16. Eric C. Tassone & Marie Lynn Miranda & Alan E. Gelfand, 2010. "Disaggregated spatial modelling for areal unit categorical data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(1), pages 175-190, January.
  17. Lawrence N Kazembe, 2013. "A Bayesian Two Part Model Applied to Analyze Risk Factors of Adult Mortality with Application to Data from Namibia," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-10, September.
  18. Xiaoping Jin & Sudipto Banerjee & Bradley P. Carlin, 2007. "Order‐free co‐regionalized areal data models with application to multiple‐disease mapping," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 817-838, November.
  19. Ippoliti, L. & Martin, R.J. & Romagnoli, L., 2018. "Efficient likelihood computations for some multivariate Gaussian Markov random fields," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 185-200.
  20. Lan Hu & Daniel A. Griffith & Yongwan Chun, 2018. "Space-Time Statistical Insights about Geographic Variation in Lung Cancer Incidence Rates: Florida, USA, 2000–2011," IJERPH, MDPI, vol. 15(11), pages 1-18, October.
  21. Zhu, Dongping & Huang, Xiaogang & Ding, Zhixia & Zhang, Wei, 2024. "Estimation of wind turbine responses with attention-based neural network incorporating environmental uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
  22. Brian J. Reich & James S. Hodges, 2008. "Modeling Longitudinal Spatial Periodontal Data: A Spatially Adaptive Model with Tools for Specifying Priors and Checking Fit," Biometrics, The International Biometric Society, vol. 64(3), pages 790-799, September.
  23. Carlos García & Zaida Quiroz & Marcos Prates, 2023. "Bayesian spatial quantile modeling applied to the incidence of extreme poverty in Lima–Peru," Computational Statistics, Springer, vol. 38(2), pages 603-621, June.
  24. Angel G. Ortiz & Daniel Wiese & Kristen A. Sorice & Minhhuyen Nguyen & Evelyn T. González & Kevin A. Henry & Shannon M. Lynch, 2020. "Liver Cancer Incidence and Area-Level Geographic Disparities in Pennsylvania—A Geo-Additive Approach," IJERPH, MDPI, vol. 17(20), pages 1-20, October.
  25. Pan, Chun & Cai, Bo & Wang, Lianming & Lin, Xiaoyan, 2014. "Bayesian semiparametric model for spatially correlated interval-censored survival data," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 198-208.
  26. Daniel Wiese & Antoinette M. Stroup & Alina Shevchenko & Sylvia Hsu & Kevin A. Henry, 2023. "Disparities in Cutaneous T-Cell Lymphoma Incidence by Race/Ethnicity and Area-Based Socioeconomic Status," IJERPH, MDPI, vol. 20(4), pages 1-10, February.
  27. Sain, Stephan R. & Cressie, Noel, 2007. "A spatial model for multivariate lattice data," Journal of Econometrics, Elsevier, vol. 140(1), pages 226-259, September.
  28. Susanne Gschlößl & Claudia Czado, 2008. "Modelling count data with overdispersion and spatial effects," Statistical Papers, Springer, vol. 49(3), pages 531-552, July.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.