IDEAS home Printed from https://ideas.repec.org/a/spr/sistpr/v17y2014i3p283-294.html
   My bibliography  Save this article

Misparametrization subsets for penalized least squares model selection

Author

Listed:
  • Xavier Guyon
  • Cécile Hardouin

Abstract

Identifying a model by the penalized contrast procedure, we give an analytical estimation of misfitting subsets in the specific case of a least squares contrast. Then, specifying the statistical model, this allows to determine penalization rates ensuring a consistent identification. Applications are given to time series and geostatistical identification. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Xavier Guyon & Cécile Hardouin, 2014. "Misparametrization subsets for penalized least squares model selection," Statistical Inference for Stochastic Processes, Springer, vol. 17(3), pages 283-294, October.
    • Handle: RePEc:spr:sistpr:v:17:y:2014:i:3:p:283-294
    DOI: 10.1007/s11203-014-9100-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11203-014-9100-y
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11203-014-9100-y?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. Jean-Marc Bardet & Paul Doukhan & José León, 2008. "A functional limit theorem for η-weakly dependent processes and its applications," Statistical Inference for Stochastic Processes, Springer, vol. 11(3), pages 265-280, October.
    2. Doukhan, Paul & Louhichi, Sana, 1999. "A new weak dependence condition and applications to moment inequalities," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 313-342, December.
    3. Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 21(1), pages 243-247, December.
    4. Bai, Z. D. & Subramanyam, K. & Zhao, L. C., 1988. "On determination of the order of an autoregressive model," Journal of Multivariate Analysis, Elsevier, vol. 27(1), pages 40-52, October.
    5. Guyon, Xavier & Yao, Jian-feng, 1999. "On the Underfitting and Overfitting Sets of Models Chosen by Order Selection Criteria," Journal of Multivariate Analysis, Elsevier, vol. 70(2), pages 221-249, August.
    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. Giovanna Jona Lasinio & Francesco Lagona, 2002. "Selection of the neighborhood structure for space-time Markov random field models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(3), pages 293-311, October.
    2. Guyon, Xavier & Yao, Jian-feng, 1999. "On the Underfitting and Overfitting Sets of Models Chosen by Order Selection Criteria," Journal of Multivariate Analysis, Elsevier, vol. 70(2), pages 221-249, August.
    3. El Ghouch, Anouar & Genton, Marc G. & Bouezmarni , Taoufik, 2012. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," LIDAM Discussion Papers ISBA 2012001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Campos, Eduardo Lima & Cysne, Rubens Penha, 2017. "A time-varying fiscal reaction function for Brazil," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 795, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    5. Jerôme Dedecker & Paul Doukhan, 2002. "A New Covariance Inequality and Applications," Working Papers 2002-25, Center for Research in Economics and Statistics.
    6. Rodrigo Hakim das Neves, 2020. "Bitcoin pricing: impact of attractiveness variables," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-18, December.
    7. Asghar, Zahid & Abid, Irum, 2007. "Performance of lag length selection criteria in three different situations," MPRA Paper 40042, University Library of Munich, Germany.
    8. Kathryn M. Dominguez, 1991. "Do Exchange Auctions Work? An Examination of the Bolivian Experience," NBER Working Papers 3683, National Bureau of Economic Research, Inc.
    9. Pierre Perron & Eduardo Zorita & Wen Cao & Clifford Hurvich & Philippe Soulier, 2017. "Drift in Transaction-Level Asset Price Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 769-790, September.
    10. Bin Liu & Weifeng Chen & Bo Li & Xiuping Liu, 2022. "Neural Subspace Learning for Surface Defect Detection," Mathematics, MDPI, vol. 10(22), pages 1-16, November.
    11. Jacint Balaguer & Manuel Cantavella-Jorda, 2004. "Structural change in exports and economic growth: cointegration and causality analysis for Spain (1961-2000)," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 473-477.
    12. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Sep 2024.
    13. Muhammad Farooq Arby & Amjad Ali, 2017. "Threshold Inflation in Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 13, pages 1-19.
    14. Ramona Dumitriu & Razvan Stefanescu, 2015. "The Relationship Between Romanian Exports And Economic Growth After The Adhesion To European Union," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 17-26.
    15. David F. Hendry & Hans-Martin Krolzig, 2005. "The Properties of Automatic "GETS" Modelling," Economic Journal, Royal Economic Society, vol. 115(502), pages C32-C61, 03.

    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:sistpr:v:17:y:2014:i:3:p:283-294. 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.