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Bayesian Variable Selection for Multivariate Spatially Varying Coefficient Regression

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  • Brian J. Reich
  • Montserrat Fuentes
  • Amy H. Herring
  • Kelly R. Evenson

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  • Brian J. Reich & Montserrat Fuentes & Amy H. Herring & Kelly R. Evenson, 2010. "Bayesian Variable Selection for Multivariate Spatially Varying Coefficient Regression," Biometrics, The International Biometric Society, vol. 66(3), pages 772-782, September.
    • Handle: RePEc:bla:biomet:v:66:y:2010:i:3:p:772-782
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01333.x
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    References listed on IDEAS

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    1. Smith, Michael & Fahrmeir, Ludwig, 2007. "Spatial Bayesian Variable Selection With Application to Functional Magnetic Resonance Imaging," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 417-431, June.
    2. Huang, Hsin-Cheng & Chen, Chun-Shu, 2007. "Optimal Geostatistical Model Selection," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1009-1024, September.
    3. Zhang, Min & Strawderman, Robert L. & Cowen, Mark E. & Wells, Martin T., 2006. "Bayesian Inference for a Two-Part Hierarchical Model: An Application to Profiling Providers in Managed Health Care," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 934-945, September.
    4. Ross, Catherine E., 2000. "Walking, exercising, and smoking: does neighborhood matter?," Social Science & Medicine, Elsevier, vol. 51(2), pages 265-274, July.
    5. Paul S. Albert & Joannie Shen, 2005. "Modelling longitudinal semicontinuous emesis volume data with serial correlation in an acupuncture clinical trial," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(4), pages 707-720, August.
    6. Brian J. Reich & James S. Hodges & Vesna Zadnik, 2006. "Effects of Residual Smoothing on the Posterior of the Fixed Effects in Disease-Mapping Models," Biometrics, The International Biometric Society, vol. 62(4), pages 1197-1206, December.
    7. Paciorek, Christopher J., 2007. "Computational techniques for spatial logistic regression with large data sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3631-3653, May.
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    Cited by:

    1. Zhong, Yan & Sang, Huiyan & Cook, Scott J. & Kellstedt, Paul M., 2023. "Sparse spatially clustered coefficient model via adaptive regularization," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    2. Guanyu Hu & Yishu Xue & Fred Huffer, 2021. "A Comparison of Bayesian Accelerated Failure Time Models with Spatially Varying Coefficients," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 541-557, November.
    3. Hu, Guanyu, 2021. "Spatially varying sparsity in dynamic regression models," Econometrics and Statistics, Elsevier, vol. 17(C), pages 23-34.
    4. Laura F. Boehm Vock & Brian J. Reich & Montserrat Fuentes & Francesca Dominici, 2015. "Spatial variable selection methods for investigating acute health effects of fine particulate matter components," Biometrics, The International Biometric Society, vol. 71(1), pages 167-177, March.
    5. Wenning Feng & Abdhi Sarkar & Chae Young Lim & Tapabrata Maiti, 2016. "Variable selection for binary spatial regression: Penalized quasi‐likelihood approach," Biometrics, The International Biometric Society, vol. 72(4), pages 1164-1172, December.
    6. Guanyu Hu & Yishu Xue & Zhihua Ma, 2020. "Bayesian Clustered Coefficients Regression with Auxiliary Covariates Assistant Random Effects," Papers 2004.12022, arXiv.org, revised Aug 2021.

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