IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v34y2000i4p387-413.html

Importance sampling in Bayesian networks using probability trees

Author

Listed:
  • Salmeron, Antonio
  • Cano, Andres
  • Moral, Serafin

Abstract

No abstract is available for this item.

Suggested Citation

  • Salmeron, Antonio & Cano, Andres & Moral, Serafin, 2000. "Importance sampling in Bayesian networks using probability trees," Computational Statistics & Data Analysis, Elsevier, vol. 34(4), pages 387-413, October.
  • Handle: RePEc:eee:csdana:v:34:y:2000:i:4:p:387-413
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(99)00110-3
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    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. Pedro Bonilla-Nadal & Andrés Cano & Manuel Gómez-Olmedo & Serafín Moral & Ofelia Paula Retamero, 2022. "Using Value-Based Potentials for Making Approximate Inference on Probabilistic Graphical Models," Mathematics, MDPI, vol. 10(14), pages 1-27, July.
    2. Tien, Iris & Der Kiureghian, Armen, 2016. "Algorithms for Bayesian network modeling and reliability assessment of infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 134-147.

    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. Bryan S. Graham & Andrin Pelican, 2023. "Scenario Sampling for Large Supermodular Games," Papers 2307.11857, arXiv.org.
    2. Boneva, Teodora & Golin, Marta & Kaufmann, Katja Maria & Rauh, Christopher, 2022. "Beliefs about Maternal Labor Supply," IZA Discussion Papers 15788, Institute of Labor Economics (IZA).
    3. Fernandez-Cornejo, Jorge & Wechsler, Seth James, 2012. "Fifteen Years Later: Examining the Adoption of Bt Corn Varieties by U.S. Farmers," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124257, Agricultural and Applied Economics Association.
    4. Cranfield, John A.L. & Preckel, Paul V. & Liu, Songquan, 1997. "Approximating Bayesian Posteriors using Multivariate Gaussian Quadrature," 1997 Annual Meeting, July 13-16, 1997, Reno\ Sparks, Nevada 35791, Western Agricultural Economics Association.
    5. Khazri, Afifa, 1999. "Contrats salariaux, rétention de main-d’œuvre et cycle économique [Wage Contracts, Labor Retention and Economic Cycle]," MPRA Paper 86755, University Library of Munich, Germany.
    6. Ardia, David & Hoogerheide, Lennart F., 2010. "Efficient Bayesian estimation and combination of GARCH-type models," MPRA Paper 22919, University Library of Munich, Germany.
    7. Roman Liesenfeld & Jean-Francois Richard, 2006. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 335-360.
    8. Uhlig, H.F.H.V.S., 1996. "Bayesian Vector Autoregressions with Stochastic Volatility," Other publications TiSEM 4fd55395-6830-46a2-9d18-e, Tilburg University, School of Economics and Management.
    9. Holloway, Garth J. & Hertel, Thomas W., 1991. "Comparing Hypotheses About Competition," Working Papers 225867, University of California, Davis, Department of Agricultural and Resource Economics.
    10. Yang Fuyu & Leon-Gonzalez Roberto, 2010. "Bayesian Estimation and Model Selection in the Generalized Stochastic Unit Root Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-38, September.
    11. Koopman, Siem Jan & Lucas, André, 2008. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 510-525.
    12. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    13. Goldman Elena & Tsurumi Hiroki, 2005. "Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-38, June.
    14. Arnaud Dufays, 2016. "Evolutionary Sequential Monte Carlo Samplers for Change-Point Models," Econometrics, MDPI, vol. 4(1), pages 1-33, March.
    15. Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2009. "Adaptive Mixture of Student-t Distributions as a Flexible Candidate Distribution for Efficient Simulation: The R Package AdMit," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i03).
    16. İsmail Başoğlu & Wolfgang Hörmann & Halis Sak, 2018. "Efficient simulations for a Bernoulli mixture model of portfolio credit risk," Annals of Operations Research, Springer, vol. 260(1), pages 113-128, January.
    17. Borowska, Agnieszka & Hoogerheide, Lennart & Koopman, Siem Jan & van Dijk, Herman K., 2020. "Partially censored posterior for robust and efficient risk evaluation," Journal of Econometrics, Elsevier, vol. 217(2), pages 335-355.
    18. Davide Pettenuzzo & Allan G. Timmermann & Rossen I. Valkanov, 2008. "Return Predictability under Equilibrium Constraints on the Equity Premium," Working Papers 37, Brandeis University, Department of Economics and International Business School.
    19. Spotts, Harlan E. & Weinberger, Marc G. & Assaf, A. George & Weinberger, Michelle F., 2022. "The role of paid media, earned media, and sales promotions in driving marcom sales performance in consumer services," Journal of Business Research, Elsevier, vol. 152(C), pages 387-397.

    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:eee:csdana:v:34:y:2000:i:4:p:387-413. 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.elsevier.com/locate/csda .

    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.