IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v31y2016i3d10.1007_s00180-016-0662-6.html
   My bibliography  Save this article

Diagnostic Robust Generalized Potential Based on Index Set Equality (DRGP (ISE)) for the identification of high leverage points in linear model

Author

Listed:
  • Hock Ann Lim

    (Infrastructure University Kuala Lumpur)

  • Habshah Midi

    (University Putra Malaysia)

Abstract

High leverage points have tremendous effect in linear regression analysis. When a group of high leverage points is present in a dataset, the existing detection methods fail to detect them correctly. This problem is due to the masking and swamping effects. We propose the Diagnostic Robust Generalized Potentials Based on Index Set Equality (DRGP(ISE)) in this regard. The DRGP(ISE) takes off from the Diagnostic Robust Generalized Potential Based on Minimum Volume Ellipsoid (DRGP(MVE)). However, the running time of ISE is much faster than MVE. Monte Carlo simulation study and numerical data indicate that DRGP(ISE) works excellently to detect the actual high leverage points and reduce masking and swamping effects in a linear model.

Suggested Citation

  • Hock Ann Lim & Habshah Midi, 2016. "Diagnostic Robust Generalized Potential Based on Index Set Equality (DRGP (ISE)) for the identification of high leverage points in linear model," Computational Statistics, Springer, vol. 31(3), pages 859-877, September.
  • Handle: RePEc:spr:compst:v:31:y:2016:i:3:d:10.1007_s00180-016-0662-6
    DOI: 10.1007/s00180-016-0662-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-016-0662-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00180-016-0662-6?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. M. Habshah & M. R. Norazan & A.H.M. Rahmatullah Imon, 2009. "The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(5), pages 507-520.
    2. Hadi, Ali S., 1992. "A new measure of overall potential influence in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 14(1), pages 1-27, June.
    3. Sudhanshu Kumar MISHRA, 2008. "A New Method Of Robust Linear Regression Analysis: Some Monte Carlo Experiments," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(3(5)_Fall), pages 261-268.
    Full references (including those not matched with items on IDEAS)

    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. A.A.M. Nurunnabi & M. Nasser & A.H.M.R. Imon, 2016. "Identification and classification of multiple outliers, high leverage points and influential observations in linear regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(3), pages 509-525, March.
    2. A. H. M. Rahmatullah Imon, 2005. "Identifying multiple influential observations in linear regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(9), pages 929-946.
    3. repec:spo:wpmain:info:hdl:2441/5su81hd0ma8soqp1nvf7852ffv is not listed on IDEAS
    4. Julia Cage, 2015. "Measuring Policy Performance: Can We Do Better than the World Bank?," Post-Print hal-03392964, HAL.
    5. Julia Cage, 2009. "Asymmetric information, rent extraction and aid efficiency," PSE Working Papers halshs-00575055, HAL.
    6. Billor, Nedret & Hadi, Ali S. & Velleman, Paul F., 2000. "BACON: blocked adaptive computationally efficient outlier nominators," Computational Statistics & Data Analysis, Elsevier, vol. 34(3), pages 279-298, September.
    7. Barranco-Chamorro, I. & Jiménez-Gamero, M.D. & Moreno-Rebollo, J.L. & Muñoz-Pichardo, J.M., 2012. "Case-deletion type diagnostics for calibration estimators in survey sampling," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2219-2236.
    8. Hoeting, Jennifer & Raftery, Adrian E. & Madigan, David, 1996. "A method for simultaneous variable selection and outlier identification in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 22(3), pages 251-270, July.
    9. repec:hal:spmain:info:hdl:2441/5su81hd0ma8soqp1nvf7852ffv is not listed on IDEAS
    10. Cagé Julia, 2014. "Improving upon the World Bank’s Country Policy and Institutional Assessment: A New Performance Indicator Based on Aid Effectiveness," Journal of Globalization and Development, De Gruyter, vol. 5(2), pages 213-233, December.
    11. Vilijandas Bagdonavičius & Linas Petkevičius, 2020. "A new multiple outliers identification method in linear regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(3), pages 275-296, April.
    12. Egger, Peter & Winner, Hannes, 2006. "How Corruption Influences Foreign Direct Investment: A Panel Data Study," Economic Development and Cultural Change, University of Chicago Press, vol. 54(2), pages 459-486, January.
    13. Xavier Cirera & Francesca Foliano & Michael Gasiorek, 2016. "The impact of preferences on developing countries’ exports to the European Union: bilateral gravity modelling at the product level," Empirical Economics, Springer, vol. 50(1), pages 59-102, February.
    14. Kondylis, Athanassios & Hadi, Ali S., 2006. "Derived components regression using the BACON algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 556-569, November.
    15. M. Suárez-Rancel & Miguel González-Sierra, 2000. "Local and deletion diagnostic," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 9(2), pages 345-352, December.
    16. Irmak Acarlar & Harun Kınacı & Vadoud Najjari, 2014. "A New Measure for Detecting Influential DMUs in DEA," Journal of Optimization, Hindawi, vol. 2014, pages 1-7, October.
    17. Mar Reguant & Meredith Fowlie, 2017. "Measuring and Mitigating Leakage Risk," 2017 Meeting Papers 383, Society for Economic Dynamics.
    18. A.A.M. Nurunnabi & Ali S. Hadi & A.H.M.R. Imon, 2014. "Procedures for the identification of multiple influential observations in linear regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1315-1331, June.
    19. Munoz-Pichardo, J. M. & Enguix-Gonzalez, A. & Munoz-Garcia, J. & Pascual-Acosta, A., 2004. "The Frechet's metric as a measure of influence in multivariate linear models with random errors elliptically distributed," Computational Statistics & Data Analysis, Elsevier, vol. 46(3), pages 469-491, June.
    20. Julia Cage, 2015. "Measuring Policy Performance: Can We Do Better than the World Bank?," SciencePo Working papers hal-03392964, HAL.
    21. M. D. Jimenez Gamero & J. M. Munoz Pichardo & J. Munoz Garcia & A. Pascual Acosta, 2002. "Rao distance as a measure of influence in the multivariate linear model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(6), pages 841-854.
    22. Xavier Cirera, 2014. "Who captures the price rent? The impact of European Union trade preferences on export prices," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 150(3), pages 507-527, August.

    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:spr:compst:v:31:y:2016:i:3:d:10.1007_s00180-016-0662-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.