Bayesian analysis for penalized spline regression using WinBUGS

被引:0
|
作者
Crainiceanu, CM
Ruppert, D
Wand, MP
机构
[1] Johns Hopkins Univ, Dept Biostat, Baltimore, MD 21205 USA
[2] Cornell Univ, Sch Operat Res & Ind Engn, Ithaca, NY 14853 USA
[3] Univ New S Wales, Sch Math, Dept Stat, Sydney, NSW 2052, Australia
来源
JOURNAL OF STATISTICAL SOFTWARE | 2005年 / 14卷 / 14期
关键词
MCMC; semiparametric regression;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in WinBUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.
引用
收藏
页数:24
相关论文
共 50 条
  • [21] A SAS Interface for Bayesian Analysis With WinBUGS
    Zhang, Zhiyong
    McArdle, John J.
    Wang, Lijuan
    Hamagami, Fumiaki
    [J]. STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2008, 15 (04) : 705 - 728
  • [22] Bayesian analysis of dynamic panel data by penalized quantile regression
    Ali Aghamohammadi
    [J]. Statistical Methods & Applications, 2018, 27 : 91 - 108
  • [23] Data-driven selection of the spline dimension in penalized spline regression
    Kauermann, Goeran
    Opsomer, Jean D.
    [J]. BIOMETRIKA, 2011, 98 (01) : 225 - 230
  • [24] Sensitivity analysis in classification using Bayesian smoothing spline ANOVA probit regression
    Zhang, Chunzhe
    Storlie, Curtis B.
    Lee, Thomas C. M.
    [J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2022, 50 (03): : 928 - 950
  • [25] Bayesian analysis of dynamic panel data by penalized quantile regression
    Aghamohammadi, Ali
    [J]. STATISTICAL METHODS AND APPLICATIONS, 2018, 27 (01): : 91 - 108
  • [26] Shrinkage priors for Bayesian penalized regression
    van Erp, Sara
    Oberski, Daniel L.
    Mulder, Joris
    [J]. JOURNAL OF MATHEMATICAL PSYCHOLOGY, 2019, 89 : 31 - 50
  • [27] Bayesian penalized spline models for the analysis of spatio-temporal count data
    Bauer, Cici
    Wakefield, Jon
    Rue, Havard
    Self, Steve
    Feng, Zijian
    Wang, Yu
    [J]. STATISTICS IN MEDICINE, 2016, 35 (11) : 1848 - 1865
  • [28] Exploring US Business Cycles with Bivariate Loops Using Penalized Spline Regression
    Kauermann, Goeran
    Teuber, Timo
    Flaschel, Peter
    [J]. COMPUTATIONAL ECONOMICS, 2012, 39 (04) : 409 - 427
  • [29] Exploring US Business Cycles with Bivariate Loops Using Penalized Spline Regression
    Göran Kauermann
    Timo Teuber
    Peter Flaschel
    [J]. Computational Economics, 2012, 39 : 409 - 427
  • [30] Non-parametric small area estimation using penalized spline regression
    Opsomer, J. D.
    Claeskens, G.
    Ranalli, M. G.
    Kauermann, G.
    Breidt, F. J.
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2008, 70 : 265 - 286