IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v381y2007icp71-81.html
   My bibliography  Save this article

Parameter estimation for random dynamical systems using slice sampling

Author

Listed:
  • Hatjispyros, S.J.
  • Nicoleris, Theodoros
  • Walker, Stephen G.

Abstract

We provide details on the full reconstruction of the dynamic equations from measured time series data, given the general class of the underlying physical process. Our results can be used by researchers in physical modelling and statistical mechanics interested in an efficient estimation of low dimensional models, incorporating dynamic as well as observational noise. Our approach is Bayesian, based on an auxiliary variables algorithm that is fast and accurate, and direct, in the sense that only uniform distributions need to be sampled. This method is simpler than other Bayesian approaches where one has to sample from non-standard–unknown distributions using MCMC methods.

Suggested Citation

  • Hatjispyros, S.J. & Nicoleris, Theodoros & Walker, Stephen G., 2007. "Parameter estimation for random dynamical systems using slice sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 71-81.
  • Handle: RePEc:eee:phsmap:v:381:y:2007:i:c:p:71-81
    DOI: 10.1016/j.physa.2007.03.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437107002993
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2007.03.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. P. Damlen & J. Wakefield & S. Walker, 1999. "Gibbs sampling for Bayesian non‐conjugate and hierarchical models by using auxiliary variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 331-344, April.
    2. Schenk-Hoppe, Klaus Reiner, 2005. "Poverty traps and business cycles in a stochastic overlapping generations economy with S-shaped law of motion," Journal of Macroeconomics, Elsevier, vol. 27(2), pages 275-288, June.
    3. Hatjispyros, S.J. & Yannacopoulos, A.N., 2005. "A random dynamical system model of a stylized equity market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 347(C), pages 583-612.
    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. Hatjispyros, Spyridon J. & Nicoleris, Theodoros & Walker, Stephen G., 2011. "Dependent mixtures of Dirichlet processes," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2011-2025, June.
    2. Hatjispyros, Spyridon J. & Nicoleris, Theodoros & Walker, Stephen G., 2009. "A Bayesian nonparametric study of a dynamic nonlinear model," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 3948-3956, October.

    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. Hatjispyros, Spyridon J. & Nicoleris, Theodoros & Walker, Stephen G., 2009. "A Bayesian nonparametric study of a dynamic nonlinear model," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 3948-3956, October.
    2. Stephen G. Walker, 2006. "Sampling the Dirichlet Mixture Model with Slices," ICER Working Papers - Applied Mathematics Series 16-2006, ICER - International Centre for Economic Research.
    3. Marcin Kacperczyk & Paul Damien & Stephen G. Walker, 2013. "A new class of Bayesian semi-parametric models with applications to option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 967-980, May.
    4. Kazuo Nishimura & Ryszard Rudnicki & John Stachurski, 2012. "Stochastic Optimal Growth with Nonconvexities," Springer Books, in: John Stachurski & Alain Venditti & Makoto Yano (ed.), Nonlinear Dynamics in Equilibrium Models, edition 127, chapter 0, pages 261-288, Springer.
    5. Ho, Chi-san & Damien, Paul & Walker, Stephen, 2017. "Bayesian mode regression using mixtures of triangular densities," Journal of Econometrics, Elsevier, vol. 197(2), pages 273-283.
    6. Elliott, Robert J. & Chen, Zhiping & Duan, Qihong, 2009. "Insurance claims modulated by a hidden Brownian marked point process," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 163-172, October.
    7. Seongil Jo & Taeyoung Roh & Taeryon Choi, 2016. "Bayesian spectral analysis models for quantile regression with Dirichlet process mixtures," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 177-206, March.
    8. Ausín, M. Concepción & Galeano, Pedro & Ghosh, Pulak, 2014. "A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation," European Journal of Operational Research, Elsevier, vol. 232(2), pages 350-358.
    9. Shively, Thomas S. & Walker, Stephen G. & Damien, Paul, 2011. "Nonparametric function estimation subject to monotonicity, convexity and other shape constraints," Journal of Econometrics, Elsevier, vol. 161(2), pages 166-181, April.
    10. Stephen Walker, 1999. "The uniform power distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(4), pages 509-517.
    11. Daziano, Ricardo A., 2013. "Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range," Resource and Energy Economics, Elsevier, vol. 35(3), pages 429-450.
    12. Bruno J.D. Jacobs & Bas Donkers & Dennis Fok, 2016. "Model-Based Purchase Predictions for Large Assortments," Marketing Science, INFORMS, vol. 35(3), pages 389-404, May.
    13. Paap, Richard & van Nierop, Erjen & van Heerde, Harald J. & Wedel, Michel & Franses, Philip Hans & Alsem, Karel Jan, 2005. "Consideration sets, intentions and the inclusion of "don't know" in a two-stage model for voter choice," International Journal of Forecasting, Elsevier, vol. 21(1), pages 53-71.
    14. Hoogerheide, Lennart F. & Kaashoek, Johan F. & van Dijk, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks," Journal of Econometrics, Elsevier, vol. 139(1), pages 154-180, July.
    15. Chib, Siddhartha, 2004. "Markov Chain Monte Carlo Technology," Papers 2004,22, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    16. Chen, Hsiang-Chun & Wehrly, Thomas E., 2016. "Approximate uniform shrinkage prior for a multivariate generalized linear mixed model," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 148-161.
    17. Streftaris, George & Worton, Bruce J., 2008. "Efficient and accurate approximate Bayesian inference with an application to insurance data," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2604-2622, January.
    18. Hoogerheide, L.F. & van Dijk, H.K. & van Oest, R.D., 2007. "Simulation based bayesian econometric inference: principles and some recent computational advances," Econometric Institute Research Papers EI 2007-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Minjung Kyung & Jeff Gill & George Casella, 2011. "Sampling schemes for generalized linear Dirichlet process random effects models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(3), pages 259-290, August.
    20. Daniels, M.J. & Pourahmadi, M., 2009. "Modeling covariance matrices via partial autocorrelations," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2352-2363, November.

    More about this item

    Keywords

    Slice sampler; Random dynamical systems;

    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:eee:phsmap:v:381:y:2007:i:c:p:71-81. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.