IDEAS home Printed from https://ideas.repec.org/p/vic/vicewp/0903.html
   My bibliography  Save this paper

Bayesian Fuzzy Regression Analysis and Model Selection: Theory and Evidence

Author

Abstract

In this study we suggest a Bayesian approach to fuzzy clustering analysis – the Bayesian fuzzy regression. Bayesian Posterior Odds analysis is employed to select the correct number of clusters for the fuzzy regression analysis. In this study, we use a natural conjugate prior for the parameters, and we find that the Bayesian Posterior Odds provide a very powerful tool for choosing the number of clusters. The results from a Monte Carlo experiment and three illustrative applications with economic data are very encouraging.

Suggested Citation

  • Hui Feng & David E. Giles, 2009. "Bayesian Fuzzy Regression Analysis and Model Selection: Theory and Evidence," Econometrics Working Papers 0903, Department of Economics, University of Victoria.
  • Handle: RePEc:vic:vicewp:0903
    Note: ISSN 1485-6441
    as

    Download full text from publisher

    File URL: https://www.uvic.ca/socialsciences/economics/_assets/docs/econometrics/ewp0903.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Giles, David E.A. & Feng, Hui, 2005. "Output and well-being in industrialized nations in the second half of the 20th century: testing for convergence using fuzzy clustering analysis," Structural Change and Economic Dynamics, Elsevier, vol. 16(2), pages 285-308, June.
    2. Chen, Jyh-Yaw Joseph & Giles, David E.A., 2004. "Gender convergence in crime: Evidence from Canadian adult offense charge data," Journal of Criminal Justice, Elsevier, vol. 32(6), pages 593-606.
    3. David E. A. Giles & Robert Draeseke, 2001. "Econometric Modelling based on Pattern recognition via the Fuzzy c-Means Clustering Algorithm," Econometrics Working Papers 0101, Department of Economics, University of Victoria.
    4. David Giles & Chad Stroomer, 2006. "Does Trade Openness Affect the Speed of Output Convergence? Some Empirical Evidence," Empirical Economics, Springer, vol. 31(4), pages 883-903, November.
    5. David E. Giles & Chad N. Stroomer, 2004. "Identifying the Cycle of a Macroeconomic Time-Series Using Fuzzy Filtering," Econometrics Working Papers 0406, Department of Economics, University of Victoria.
    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. Hui Feng, 2011. "Forecasting comparison between two nonlinear models: fuzzy regression versus SETAR," Applied Economics Letters, Taylor & Francis Journals, vol. 18(17), pages 1623-1627.

    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. Morillas, Antonio & Díaz, Bárbara, 2007. "Qualitative Answering Surveys And Soft Computing," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(1), pages 3-19, May.
    2. Gawon Yoon, 2010. "On the performance of a nonparametric measure of convergence towards purchasing power parity in the presence of linearity," Applied Economics Letters, Taylor & Francis Journals, vol. 17(14), pages 1389-1396.
    3. Cuffaro , Miranda & Cracolici, Maria Francesca & Nijkamp, Peter, 2006. "Economic convergence vs. socio-economic convergence in space," Serie Research Memoranda 0020, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    4. Omid Ranjbar & Chien-Chiang Lee & Tsangyao Chang & Mei-Ping Chen, 2014. "Income Convergence in African Countries: Evidence from a Stationary Test With Multiple Structural Breaks," South African Journal of Economics, Economic Society of South Africa, vol. 82(3), pages 371-391, September.
    5. Maria Francesca Cracolici & Miranda Cuffaro & Peter Nijkamp, 2008. "Analysis of Spatial Disparities by a Structural Equations Model," Tinbergen Institute Discussion Papers 08-058/3, Tinbergen Institute.
    6. Ana-Maria HOLOBIUC, 2019. "Smart An Analysis Of The Real Convergence Within The European Union And Of The Well-Being Of The European Citizens," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 13(1), pages 607-614, November.
    7. David E. Giles & Chad N. Stroomer, 2004. "Identifying the Cycle of a Macroeconomic Time-Series Using Fuzzy Filtering," Econometrics Working Papers 0406, Department of Economics, University of Victoria.
    8. Hui Feng, 2011. "Forecasting comparison between two nonlinear models: fuzzy regression versus SETAR," Applied Economics Letters, Taylor & Francis Journals, vol. 18(17), pages 1623-1627.
    9. Antoni, Giacomo Degli, 2007. "Do Social Relations Affect Economic Welfare? A Microeconomic Empirical Analysis," Knowledge, Technology, Human Capital Working Papers 9330, Fondazione Eni Enrico Mattei (FEEM).
    10. Isabel Gallego-Álvarez & Mª Galindo-Villardón & Miguel Rodríguez-Rosa, 2015. "Analysis of the Sustainable Society Index Worldwide: A Study from the Biplot Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 120(1), pages 29-65, January.
    11. Welsch, Heinz & Bonn, Udo, 2008. "Economic convergence and life satisfaction in the European Union," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(3), pages 1153-1167, June.
    12. Marcos Sanso-Navarro & María Vera-Cabello & Miguel Puente-Ajovín, 2020. "Regional convergence and spatial dependence: a worldwide perspective," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(1), pages 147-177, August.
    13. repec:aut:wpaper:201706 is not listed on IDEAS
    14. knani, ramzi & fredj, ali, 2010. "Mondialisation et fluctuations des cycles économiques [globalisation and business cycle fluctuation]," MPRA Paper 22755, University Library of Munich, Germany.
    15. Joseph LiPuma & Scott Newbert & Jonathan Doh, 2013. "The effect of institutional quality on firm export performance in emerging economies: a contingency model of firm age and size," Small Business Economics, Springer, vol. 40(4), pages 817-841, May.
    16. Miranda Cuffaro & Maria Francesca Cracolici & Peter Nijkamp, 2008. "Measuring the Performance of Italian Regions on Social and Economic Dimensions," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2008(1), pages 5-25.
    17. Shepherd, David & Shi, Francis K.C., 2006. "Fuzzy modelling and estimation of economic relationships," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 417-433, November.
    18. Chad Stroomer & David E.A. Giles, 2003. "Income Convergence and trade Openness: Fuzzy Clustering and Time Series Evidence," Econometrics Working Papers 0304, Department of Economics, University of Victoria.
    19. Bowles, Roger Arthur & Florackis, Chrisostomos, 2007. "Duration of the time to reconviction: Evidence from UK prisoner discharge data," Journal of Criminal Justice, Elsevier, vol. 35(4), pages 365-378.
    20. David Giles & Chad Stroomer, 2006. "Does Trade Openness Affect the Speed of Output Convergence? Some Empirical Evidence," Empirical Economics, Springer, vol. 31(4), pages 883-903, November.
    21. Amir Safari & Detlef Seese, 2009. "Non-parametric estimation of a multiscale CHARN model using SVR," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 105-121.

    More about this item

    Keywords

    Bayesian posterior odds; model selection; fuzzy regression; fuzzy clustering;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:vic:vicewp:0903. 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: Kali Moon (email available below). General contact details of provider: https://edirc.repec.org/data/devicca.html .

    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.