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Bayesian hierarchical linear mixed models for additive smoothing splines

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  • Dongchu Sun
  • Paul Speckman

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  • Dongchu Sun & Paul Speckman, 2008. "Bayesian hierarchical linear mixed models for additive smoothing splines," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(3), pages 499-517, September.
  • Handle: RePEc:spr:aistmt:v:60:y:2008:i:3:p:499-517
    DOI: 10.1007/s10463-007-0127-3
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    References listed on IDEAS

    as
    1. Ludwig Fahrmeir & Stefan Lang, 2001. "Bayesian inference for generalized additive mixed models based on Markov random field priors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(2), pages 201-220.
    2. Paul L. Speckman, 2003. "Fully Bayesian spline smoothing and intrinsic autoregressive priors," Biometrika, Biometrika Trust, vol. 90(2), pages 289-302, June.
    3. Carter, C.K. & Kohn, R., "undated". "Markov Chain Monte Carlo in Conditionally Gaussian State Space Models," Statistics Working Paper _003, Australian Graduate School of Management.
    4. Wong, Chi-ming & Kohn, Robert, 1996. "A Bayesian approach to additive semiparametric regression," Journal of Econometrics, Elsevier, vol. 74(2), pages 209-235, October.
    5. Sally Wood & Robert Kohn & Tom Shively & Wenxin Jiang, 2002. "Model selection in spline nonparametric regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(1), pages 119-139, January.
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    Citations

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    Cited by:

    1. Yu Yue & Paul Speckman & Dongchu Sun, 2012. "Priors for Bayesian adaptive spline smoothing," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 577-613, June.
    2. Tong, Xiaojun & He, Zhuoqiong Chong & Sun, Dongchu, 2018. "Estimating Chinese Treasury yield curves with Bayesian smoothing splines," Econometrics and Statistics, Elsevier, vol. 8(C), pages 94-124.
    3. Cheng, Chin-I. & Speckman, Paul L., 2012. "Bayesian smoothing spline analysis of variance," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3945-3958.

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