IDEAS home Printed from https://ideas.repec.org/a/bla/istatr/v78y2010i2p209-215.html
   My bibliography  Save this article

Anomalies in the Foundations of Ridge Regression: Some Clarifications

Author

Listed:
  • Prasenjit Kapat
  • Prem K. Goel

Abstract

Several anomalies in the foundations of ridge regression from the perspective of constrained least‐square (LS) problems were pointed out in Jensen & Ramirez. Some of these so‐called anomalies, attributed to the non‐monotonic behaviour of the norm of unconstrained ridge estimators and the consequent lack of sufficiency of Lagrange's principle, are shown to be incorrect. It is noted in this paper that, for a fixed Y, norms of unconstrained ridge estimators corresponding to the given basis are indeed strictly monotone. Furthermore, the conditions for sufficiency of Lagrange's principle are valid for a suitable range of the constraint parameter. The discrepancy arose in the context of one data set due to confusion between estimates of the parameter vector, β, corresponding to different parametrization (choice of bases) and/or constraint norms. In order to avoid such confusion, it is suggested that the parameter β corresponding to each basis be labelled appropriately. Plusieurs anomalies ont été récemment relevées par Jensen et Ramirez (2008) dans les fondements théoriques de la “ridge regression” considérée dans une perspective de moindres carrés constraints. Certaines de ces anomalies ont été attribuées au comportement non monotone de la norme des “ridge‐estimateurs” non contraints, ainsi qu'au caractère non suffisant du principe de Lagrange. Nous indiquons dans cet article que, pour une valeur fixée de Y, la norme des ridge‐estimateurs correspondant à une base donnée sont strictement monotones. En outre, les conditions assurant le caractère suffisant du principe de Lagrange sont satisfaites pour un ensemble adéquat de valeurs du paramètre contraint. L'origine des anomalies relevées se trouve donc ailleurs. Cette apparente contradiction prend son origine, dans le contexte de l'étude d'un ensemble de données particulier, dans la confusion entre les estimateurs du vecteur de paramètres β correspondant à différentes paramétrisations (associées à différents choix d'une base) et/ou à différentes normes. Afin d'éviter ce type de confusion, il est suggéré d'indexer le paramètre de façon adéquate au moyen de la base choisie.

Suggested Citation

  • Prasenjit Kapat & Prem K. Goel, 2010. "Anomalies in the Foundations of Ridge Regression: Some Clarifications," International Statistical Review, International Statistical Institute, vol. 78(2), pages 209-215, August.
  • Handle: RePEc:bla:istatr:v:78:y:2010:i:2:p:209-215
    DOI: 10.1111/j.1751-5823.2010.00113.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1751-5823.2010.00113.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1751-5823.2010.00113.x?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
    ---><---

    References listed on IDEAS

    as
    1. Sundaram,Rangarajan K., 1996. "A First Course in Optimization Theory," Cambridge Books, Cambridge University Press, number 9780521497190, September.
    2. Sundaram,Rangarajan K., 1996. "A First Course in Optimization Theory," Cambridge Books, Cambridge University Press, number 9780521497701, September.
    3. Donald R. Jensen & Donald E. Ramirez, 2008. "Anomalies in the Foundations of Ridge Regression," International Statistical Review, International Statistical Institute, vol. 76(1), pages 89-105, April.
    4. Sylvain Sardy, 2008. "On the Practice of Rescaling Covariates," International Statistical Review, International Statistical Institute, vol. 76(2), pages 285-297, August.
    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. José García & Román Salmerón & Catalina García & María del Mar López Martín, 2016. "Standardization of Variables and Collinearity Diagnostic in Ridge Regression," International Statistical Review, International Statistical Institute, vol. 84(2), pages 245-266, August.

    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. Charles L. Munson & Lan Luo & Xiaohui Huang, 2024. "Predictive Global Sensitivity Analysis: Foundational Concepts, Tools, and Applications," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 17(4), pages 235-339, March.
    2. Brett, Craig & Weymark, John A., 2016. "Voting over selfishly optimal nonlinear income tax schedules with a minimum-utility constraint," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 18-31.
    3. Gonzalez, Stéphane & Rostom, Fatma Zahra, 2022. "Sharing the global outcomes of finite natural resource exploitation: A dynamic coalitional stability perspective," Mathematical Social Sciences, Elsevier, vol. 119(C), pages 1-10.
    4. Sawada, Hiroyuki & Yan, Xiu-Tian, 2004. "Application of Gröbner bases and quantifier elimination for insightful engineering design," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 67(1), pages 135-148.
    5. John Duggan & Joanne Roberts, 2002. "Implementing the Efficient Allocation of Pollution," American Economic Review, American Economic Association, vol. 92(4), pages 1070-1078, September.
    6. John Stachurski, 2009. "Economic Dynamics: Theory and Computation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262012774, December.
    7. Raffaella Giacomini & Toru Kitagawa, 2021. "Robust Bayesian Inference for Set‐Identified Models," Econometrica, Econometric Society, vol. 89(4), pages 1519-1556, July.
    8. Depetris Chauvin, Nicolas & Porto, Guido G., 2011. "Market Competition in Export Cash Crops and Farm Income," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126159, International Association of Agricultural Economists.
    9. Tina Kao & Flavio Menezes & John Quiggin, 2014. "Optimal access regulation with downstream competition," Journal of Regulatory Economics, Springer, vol. 45(1), pages 75-93, February.
    10. JoonHwan Cho & Thomas M. Russell, 2018. "Simple Inference on Functionals of Set-Identified Parameters Defined by Linear Moments," Papers 1810.03180, arXiv.org, revised May 2023.
    11. Nirav Mehta, 2017. "Competition In Public School Districts: Charter School Entry, Student Sorting, And School Input Determination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(4), pages 1089-1116, November.
    12. Rasch, Alexander & Wambach, Achim, 2009. "Internal decision-making rules and collusion," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 703-715, November.
    13. Achal Bassamboo & J. Michael Harrison & Assaf Zeevi, 2009. "Pointwise Stationary Fluid Models for Stochastic Processing Networks," Manufacturing & Service Operations Management, INFORMS, vol. 11(1), pages 70-89, August.
    14. Zachary Feinstein, 2015. "Financial Contagion and Asset Liquidation Strategies," Papers 1506.00937, arXiv.org, revised Nov 2016.
    15. Calthrop, Edward & Proost, Stef, 2006. "Regulating on-street parking," Regional Science and Urban Economics, Elsevier, vol. 36(1), pages 29-48, January.
    16. Brett, Craig & Weymark, John A., 2017. "Voting over selfishly optimal nonlinear income tax schedules," Games and Economic Behavior, Elsevier, vol. 101(C), pages 172-188.
    17. Park, Hyungmin, 2023. "Developmental Dictatorship and Middle Class-driven Democratisation," The Warwick Economics Research Paper Series (TWERPS) 1485, University of Warwick, Department of Economics.
    18. Dan Kovenock & Brian Roberson, 2021. "Generalizations of the General Lotto and Colonel Blotto games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 71(3), pages 997-1032, April.
    19. Gregory Besharov, 2004. "Second‐Best Considerations in Correcting Cognitive Biases," Southern Economic Journal, John Wiley & Sons, vol. 71(1), pages 12-20, July.
    20. David Sayah & Stefan Irnich, 2019. "Optimal booking control in revenue management with two substitutable resources," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(2), pages 189-222, April.

    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:bla:istatr:v:78:y:2010:i:2:p:209-215. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/isiiinl.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.