IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v72y2010i2p219-234.html
   My bibliography  Save this article

Simultaneous estimation and reduction of nonconformity in interlaboratory studies

Author

Listed:
  • William E. Strawderman
  • Andrew L. Rukhin

Abstract

Summary. Several procedures that are designed to reduce nonconformity in interlaboratory studies by shrinking data towards a consensus weighted mean are suggested. Some of them are shown to have a smaller quadratic risk than the vector sample means. Shrinkage towards a weighted mean in a random‐effects model and a statistic appearing in models which allow for systematic errors are also considered. The results are illustrated by two examples of collaborative studies.

Suggested Citation

  • William E. Strawderman & Andrew L. Rukhin, 2010. "Simultaneous estimation and reduction of nonconformity in interlaboratory studies," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(2), pages 219-234, March.
    • Handle: RePEc:bla:jorssb:v:72:y:2010:i:2:p:219-234
    DOI: 10.1111/j.1467-9868.2009.00733.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9868.2009.00733.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9868.2009.00733.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. Fourdrinier, Dominique & Strawderman, William E. & Wells, Martin T., 2003. "Robust shrinkage estimation for elliptically symmetric distributions with unknown covariance matrix," Journal of Multivariate Analysis, Elsevier, vol. 85(1), pages 24-39, April.
    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. Bodnar, Olha & Bodnar, Taras, 2021. "Objective Bayesian meta-analysis based on generalized multivariate random effects model," Working Papers 2021:5, Örebro University, School of Business.
    2. Andrew L. Rukhin, 2017. "Estimation of the common mean from heterogeneous normal observations with unknown variances," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1601-1618, November.

    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. Dominique Fourdrinier & Othmane Kortbi & William Strawderman, 2014. "Generalized Bayes minimax estimators of location vectors for spherically symmetric distributions with residual vector," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(2), pages 285-296, February.
    2. Fourdrinier, Dominique & Strawderman, William, 2014. "On the non existence of unbiased estimators of risk for spherically symmetric distributions," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 6-13.
    3. Fourdrinier, Dominique & Strawderman, William E., 2016. "Stokes’ theorem, Stein’s identity and completeness," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 224-231.
    4. Aurélie Boisbunon & Stéphane Canu & Dominique Fourdrinier & William Strawderman & Martin T. Wells, 2014. "Akaike's Information Criterion, C p and Estimators of Loss for Elliptically Symmetric Distributions," International Statistical Review, International Statistical Institute, vol. 82(3), pages 422-439, December.
    5. Bodnar, Olha & Bodnar, Taras & Parolya, Nestor, 2022. "Recent advances in shrinkage-based high-dimensional inference," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    6. Dominique Fourdrinier & William Strawderman & Martin Wells, 2006. "Estimation of a Location Parameter with Restrictions or “vague information” for Spherically Symmetric Distributions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(1), pages 73-92, March.
    7. Bodnar, Taras & Okhrin, Ostap & Parolya, Nestor, 2019. "Optimal shrinkage estimator for high-dimensional mean vector," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 63-79.
    8. Fourdrinier Dominique & Strawderman William E. & Wells Martin T., 2009. "Improved estimation for elliptically symmetric distributions with unknown block diagonal covariance matrix," Statistics & Risk Modeling, De Gruyter, vol. 26(3), pages 203-217, April.
    9. Dominique Fourdrinier & William Strawderman, 2015. "Robust minimax Stein estimation under invariant data-based loss for spherically and elliptically symmetric distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(4), pages 461-484, May.
    10. Canu, Stéphane & Fourdrinier, Dominique, 2017. "Unbiased risk estimates for matrix estimation in the elliptical case," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 60-72.
    11. Fourdrinier, Dominique & Mezoued, Fatiha & Wells, Martin T., 2016. "Estimation of the inverse scatter matrix of an elliptically symmetric distribution," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 32-55.
    12. Evgeny Pchelintsev, 2013. "Improved estimation in a non-Gaussian parametric regression," Statistical Inference for Stochastic Processes, Springer, vol. 16(1), pages 15-28, April.
    13. Karamikabir, Hamid & Afshari, Mahmoud, 2020. "Generalized Bayesian shrinkage and wavelet estimation of location parameter for spherical distribution under balance-type loss: Minimaxity and admissibility," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
    14. Wang, Cheng & Tong, Tiejun & Cao, Longbing & Miao, Baiqi, 2014. "Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 222-232.
    15. Wells, Martin T. & Zhou, Gongfu, 2008. "Generalized Bayes minimax estimators of the mean of multivariate normal distribution with unknown variance," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2208-2220, November.
    16. Besson, Olivier & Abramovich, Yuri I., 2014. "Invariance properties of the likelihood ratio for covariance matrix estimation in some complex elliptically contoured distributions," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 237-246.
    17. Fourdrinier, Dominique & Marchand, Éric & Strawderman, William E., 2019. "On efficient prediction and predictive density estimation for normal and spherically symmetric models," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 18-25.

    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:jorssb:v:72:y:2010:i:2:p:219-234. 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/rssssea.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.