IDEAS home Printed from
   My bibliography  Save this article

An efficient proposal distribution for Metropolis–Hastings using a B-splines technique


  • Shao, Wei
  • Guo, Guangbao
  • Meng, Fanyu
  • Jia, Shuqin


In this paper, we proposed an efficient proposal distribution in the Metropolis–Hastings algorithm using the B-spline proposal Metropolis–Hastings algorithm. This new method can be extended to high-dimensional cases, such as the B-spline proposal in Gibbs sampling and in the Hit-and-Run (BSPHR) algorithm. It improves the proposal distribution in the Metropolis–Hastings algorithm by carrying more information from the target function. The performance of BSPHR was compared with that of other Markov Chain Monte Carlo (MCMC) samplers in simulation and real data examples. Simulation results show that the new method performs significantly better than other MCMC methods.

Suggested Citation

  • Shao, Wei & Guo, Guangbao & Meng, Fanyu & Jia, Shuqin, 2013. "An efficient proposal distribution for Metropolis–Hastings using a B-splines technique," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 465-478.
  • Handle: RePEc:eee:csdana:v:57:y:2013:i:1:p:465-478
    DOI: 10.1016/j.csda.2012.07.014

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only.

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

    References listed on IDEAS

    1. S. Illeris & G. Akehurst, 2002. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 22(1), pages 1-3, January.
    2. Petris, Giovanni, 2010. "An R Package for Dynamic Linear Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i12).
    3. Liang F. & Wong W.H., 2001. "Real-Parameter Evolutionary Monte Carlo With Applications to Bayesian Mixture Models," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 653-666, June.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Fabrizio Leisen & Roberto Casarin & David Luengo & Luca Martino, 2013. "Adaptive Sticky Generalized Metropolis," Working Papers 2013:19, Department of Economics, University of Venice "Ca' Foscari".
    2. Aur'elien Hazan, 2017. "Stock-flow consistent macroeconomic model with nonuniform distributional constraint," Papers 1708.00645,


    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:eee:csdana:v:57:y:2013:i:1:p:465-478. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.