IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v51y2010i2p315-323.html
   My bibliography  Save this article

A new stochastic mixed ridge estimator in linear regression model

Author

Listed:
  • Yalian Li
  • Hu Yang

Abstract

No abstract is available for this item.

Suggested Citation

  • Yalian Li & Hu Yang, 2010. "A new stochastic mixed ridge estimator in linear regression model," Statistical Papers, Springer, vol. 51(2), pages 315-323, June.
    • Handle: RePEc:spr:stpapr:v:51:y:2010:i:2:p:315-323
    DOI: 10.1007/s00362-008-0169-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00362-008-0169-5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00362-008-0169-5?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. Groß, Jürgen, 2003. "Restricted ridge estimation," Statistics & Probability Letters, Elsevier, vol. 65(1), pages 57-64, October.
    2. M. Hubert & P. Wijekoon, 2006. "Improvement of the Liu estimator in linear regression model," Statistical Papers, Springer, vol. 47(3), pages 471-479, June.
    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. M. Revan Özkale & Atif Abbasi, 2022. "Iterative restricted OK estimator in generalized linear models and the selection of tuning parameters via MSE and genetic algorithm," Statistical Papers, Springer, vol. 63(6), pages 1979-2040, December.
    2. Fikri Akdeniz & Mahdi Roozbeh, 2019. "Generalized difference-based weighted mixed almost unbiased ridge estimator in partially linear models," Statistical Papers, Springer, vol. 60(5), pages 1717-1739, October.
    3. Hongchang Hu & Weifu Hu & Xinxin Yu, 2021. "Pseudo-maximum likelihood estimators in linear regression models with fractional time series," Statistical Papers, Springer, vol. 62(2), pages 639-659, April.
    4. Xinfeng Chang & Hu Yang, 2012. "Combining two-parameter and principal component regression estimators," Statistical Papers, Springer, vol. 53(3), pages 549-562, August.
    5. M. Arashi & T. Valizadeh, 2015. "Performance of Kibria’s methods in partial linear ridge regression model," Statistical Papers, Springer, vol. 56(1), pages 231-246, February.
    6. Jan Pablo Burgard & Joscha Krause & Ralf Münnich, 2019. "Penalized Small Area Models for the Combination of Unit- and Area-level Data," Research Papers in Economics 2019-05, University of Trier, Department of Economics.
    7. F. Ghapani & A. R. Rasekh & B. Babadi, 2018. "The weighted ridge estimator in stochastic restricted linear measurement error models," Statistical Papers, Springer, vol. 59(2), pages 709-723, June.
    8. Kristofer Månsson & B. M. Golam Kibria, 2021. "Estimating the Unrestricted and Restricted Liu Estimators for the Poisson Regression Model: Method and Application," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 311-326, August.
    9. Sivarajah Arumairajan & Pushpakanthie Wijekoon, 2017. "The generalized preliminary test estimator when different sets of stochastic restrictions are available," Statistical Papers, Springer, vol. 58(3), pages 729-747, September.

    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. Yalian Li & Hu Yang, 2019. "Performance of the restricted almost unbiased type principal components estimators in linear regression model," Statistical Papers, Springer, vol. 60(1), pages 19-34, February.
    2. Candelon, B. & Hurlin, C. & Tokpavi, S., 2012. "Sampling error and double shrinkage estimation of minimum variance portfolios," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 511-527.
    3. Duran, Esra Akdeniz & Härdle, Wolfgang Karl & Osipenko, Maria, 2011. "Difference based ridge and Liu type estimators in semiparametric regression models," SFB 649 Discussion Papers 2011-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. M. Revan Özkale, 2014. "The relative efficiency of the restricted estimators in linear regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(5), pages 998-1027, May.
    5. Roozbeh, Mahdi, 2018. "Optimal QR-based estimation in partially linear regression models with correlated errors using GCV criterion," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 45-61.
    6. Jahufer, Aboobacker & Jianbao, Chen, 2009. "Assessing global influential observations in modified ridge regression," Statistics & Probability Letters, Elsevier, vol. 79(4), pages 513-518, February.
    7. Sivarajah Arumairajan & Pushpakanthie Wijekoon, 2017. "The generalized preliminary test estimator when different sets of stochastic restrictions are available," Statistical Papers, Springer, vol. 58(3), pages 729-747, September.
    8. Roozbeh, M. & Arashi, M., 2013. "Feasible ridge estimator in partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 35-44.
    9. M. Revan Özkale & Atif Abbasi, 2022. "Iterative restricted OK estimator in generalized linear models and the selection of tuning parameters via MSE and genetic algorithm," Statistical Papers, Springer, vol. 63(6), pages 1979-2040, December.
    10. M. Alkhamisi, 2010. "Simulation study of new estimators combining the SUR ridge regression and the restricted least squares methodologies," Statistical Papers, Springer, vol. 51(3), pages 651-672, September.
    11. Murat Genç, 2022. "A new double-regularized regression using Liu and lasso regularization," Computational Statistics, Springer, vol. 37(1), pages 159-227, March.
    12. Akdeniz Duran, Esra & Härdle, Wolfgang Karl & Osipenko, Maria, 2012. "Difference based ridge and Liu type estimators in semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 164-175.
    13. Bahadır Yüzbaşı & S. Ejaz Ahmed, 2020. "Ridge Type Shrinkage Estimation of Seemingly Unrelated Regressions And Analytics of Economic and Financial Data from “Fragile Five” Countries," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    14. M. Revan Özkale & Hans Nyquist, 2021. "The stochastic restricted ridge estimator in generalized linear models," Statistical Papers, Springer, vol. 62(3), pages 1421-1460, June.
    15. Aboobacker Jahufer & Jianbao Chen, 2012. "Identifying local influential observations in Liu estimator," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(3), pages 425-438, April.
    16. Özkale, M. Revan, 2009. "A stochastic restricted ridge regression estimator," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1706-1716, September.
    17. Hu Yang & Jianwen Xu, 2011. "Preliminary test Liu estimators based on the conflicting W, LR and LM tests in a regression model with multivariate Student-t error," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(3), pages 275-292, May.
    18. Jianwen Xu & Hu Yang, 2011. "On the restricted almost unbiased estimators in linear regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(3), pages 605-617, November.
    19. M. Alkhamisi & I. MacNeill, 2015. "Recent results in ridge regression methods," METRON, Springer;Sapienza Università di Roma, vol. 73(3), pages 359-376, December.
    20. Hu Yang & Jianwen Xu, 2009. "An alternative stochastic restricted Liu estimator in linear regression," Statistical Papers, Springer, vol. 50(3), pages 639-647, June.

    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:stpapr:v:51:y:2010:i:2:p:315-323. 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.