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Bayesian Spatiotemporal Inference in Functional Magnetic Resonance Imaging

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  • C. Gössl
  • D. P. Auer
  • L. Fahrmeir

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  • C. Gössl & D. P. Auer & L. Fahrmeir, 2001. "Bayesian Spatiotemporal Inference in Functional Magnetic Resonance Imaging," Biometrics, The International Biometric Society, vol. 57(2), pages 554-562, June.
    • Handle: RePEc:bla:biomet:v:57:y:2001:i:2:p:554-562
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2001.00554.x
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. William D Penny & Gerard R Ridgway, 2013. "Efficient Posterior Probability Mapping Using Savage-Dickey Ratios," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-11, March.
    2. Holly, Sean & Hashem Pesaran, M. & Yamagata, Takashi, 2011. "The spatial and temporal diffusion of house prices in the UK," Journal of Urban Economics, Elsevier, vol. 69(1), pages 2-23, January.
    3. Xinchao Luo & Lixing Zhu & Hongtu Zhu, 2016. "Single‐index varying coefficient model for functional responses," Biometrics, The International Biometric Society, vol. 72(4), pages 1275-1284, December.
    4. Lee, Dae-Jin & Durbán, María, 2009. "P-spline anova-type interaction models for spatio-temporal smoothing," DES - Working Papers. Statistics and Econometrics. WS ws093312, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Michelle F. Miranda & Hongtu Zhu & Joseph G. Ibrahim, 2013. "Bayesian Spatial Transformation Models with Applications in Neuroimaging Data," Biometrics, The International Biometric Society, vol. 69(4), pages 1074-1083, December.
    6. Sarkka, Aila & Renshaw, Eric, 2006. "The analysis of marked point patterns evolving through space and time," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1698-1718, December.
    7. Paul Schmidt & Volker J Schmid & Christian Gaser & Dorothea Buck & Susanne Bührlen & Annette Förschler & Mark Mühlau, 2013. "Fully Bayesian Inference for Structural MRI: Application to Segmentation and Statistical Analysis of T2-Hypointensities," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-14, July.
    8. Schmidt, Paul & Mühlau, Mark & Schmid, Volker, 2017. "Fitting large-scale structured additive regression models using Krylov subspace methods," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 59-75.

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