IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v63y2007i3p724-732.html
   My bibliography  Save this article

Bayesian Adaptive Regression Splines for Hierarchical Data

Author

Listed:
  • Jamie L. Bigelow
  • David B. Dunson

Abstract

No abstract is available for this item.

Suggested Citation

  • Jamie L. Bigelow & David B. Dunson, 2007. "Bayesian Adaptive Regression Splines for Hierarchical Data," Biometrics, The International Biometric Society, vol. 63(3), pages 724-732, September.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:3:p:724-732
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2007.00761.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lyndia C. Brumback & Mary J. Lindstrom, 2004. "Self Modeling with Flexible, Random Time Transformations," Biometrics, The International Biometric Society, vol. 60(2), pages 461-470, June.
    2. Morris, Jeffrey S. & Vannucci, Marina & Brown, Philip J. & Carroll, Raymond J., 2003. "Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 573-583, January.
    3. Claudio J. Verzilli & John C. Whittaker & Nigel Stallard & Daniel Chasman, 2005. "A hierarchical Bayesian model for predicting the functional consequences of amino‐acid polymorphisms," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(1), pages 191-206, January.
    4. C. C. Holmes & B. K. Mallick, 2001. "Bayesian regression with multivariate linear splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 3-17.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Shashank Vaid & Michael Ahearne & Ryan Krause, 2021. "Operations‐Related Structural Flux: Firm Performance Effects of Executives’ Appointments and Exits," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2188-2210, July.
    2. Mukhoti, Sujay & Guhathakurta, Kousik, 2015. "Product market performance and capital structure: A Hierarchical Bayesian semi-parametric panel regression model," MPRA Paper 62517, University Library of Munich, Germany.
    3. Bruno Scarpa & David B. Dunson, 2009. "Bayesian Hierarchical Functional Data Analysis Via Contaminated Informative Priors," Biometrics, The International Biometric Society, vol. 65(3), pages 772-780, September.
    4. Botts, Carsten H. & Daniels, Michael J., 2008. "A flexible approach to Bayesian multiple curve fitting," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5100-5120, August.
    5. Bruno Scarpa & David B. Dunson, 2014. "Enriched Stick-Breaking Processes for Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 647-660, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Donatello Telesca & Lurdes Y.T. Inoue & Mauricio Neira & Ruth Etzioni & Martin Gleave & Colleen Nelson, 2009. "Differential Expression and Network Inferences through Functional Data Modeling," Biometrics, The International Biometric Society, vol. 65(3), pages 793-804, September.
    2. Bruno Scarpa & David B. Dunson, 2009. "Bayesian Hierarchical Functional Data Analysis Via Contaminated Informative Priors," Biometrics, The International Biometric Society, vol. 65(3), pages 772-780, September.
    3. Brian Neelon & David B. Dunson, 2004. "Bayesian Isotonic Regression and Trend Analysis," Biometrics, The International Biometric Society, vol. 60(2), pages 398-406, June.
    4. Chiara Mazzetta & Steve Brooks & Stephen N. Freeman, 2007. "On Smoothing Trends in Population Index Modeling," Biometrics, The International Biometric Society, vol. 63(4), pages 1007-1014, December.
    5. Michael R. Wierzbicki & Li-Bing Guo & Qing-Tao Du & Wensheng Guo, 2014. "Sparse Semiparametric Nonlinear Model With Application to Chromatographic Fingerprints," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1339-1349, December.
    6. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    7. Wesley K. Thompson & Ori Rosen, 2008. "A Bayesian Model for Sparse Functional Data," Biometrics, The International Biometric Society, vol. 64(1), pages 54-63, March.
    8. Wai-Yin Poon & Hai-Bin Wang, 2014. "Multivariate partially linear single-index models: Bayesian analysis," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 755-768, December.
    9. Nicoleta Serban & Ana-Maria Staicu & Raymond J. Carroll, 2013. "Multilevel Cross-Dependent Binary Longitudinal Data," Biometrics, The International Biometric Society, vol. 69(4), pages 903-913, December.
    10. Fu, Eric & Heckman, Nancy, 2019. "Model-based curve registration via stochastic approximation EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 159-175.
    11. Daniel Gervini & Patrick A. Carter, 2014. "Warped functional analysis of variance," Biometrics, The International Biometric Society, vol. 70(3), pages 526-535, September.
    12. Yehua Li & Naisyin Wang & Raymond J. Carroll, 2013. "Selecting the Number of Principal Components in Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1284-1294, December.
    13. Kyle Hasenstab & Aaron Scheffler & Donatello Telesca & Catherine A. Sugar & Shafali Jeste & Charlotte DiStefano & Damla Şentürk, 2017. "A multi-dimensional functional principal components analysis of EEG data," Biometrics, The International Biometric Society, vol. 73(3), pages 999-1009, September.
    14. Matthew Wheeler & A. John Bailer, 2012. "Monotonic Bayesian Semiparametric Benchmark Dose Analysis," Risk Analysis, John Wiley & Sons, vol. 32(7), pages 1207-1218, July.
    15. Fang Yao & Yichao Wu & Jialin Zou, 2016. "Probability-enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 1-22, March.
    16. E. Andrés Houseman & Brent A. Coull & Rebecca A. Betensky, 2006. "Feature-Specific Penalized Latent Class Analysis for Genomic Data," Biometrics, The International Biometric Society, vol. 62(4), pages 1062-1070, December.
    17. Brian J. Reich & Howard H. Chang & Kristen M. Foley, 2014. "A spectral method for spatial downscaling," Biometrics, The International Biometric Society, vol. 70(4), pages 932-942, December.
    18. Wang, Hai-Bin, 2009. "Bayesian estimation and variable selection for single index models," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2617-2627, May.
    19. Ryu Duchwan & Xu Hongyan & George Varghese & Su Shaoyong & Wang Xiaoling & Shi Huidong & Podolsky Robert H., 2016. "Differential methylation tests of regulatory regions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(3), pages 237-251, June.
    20. Zhiyong Chen & Jianbao Chen, 2022. "Bayesian analysis of partially linear, single-index, spatial autoregressive models," Computational Statistics, Springer, vol. 37(1), pages 327-353, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:63:y:2007:i:3:p:724-732. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.