IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v78y2016i1p175-191.html
   My bibliography  Save this article

Optimal designs for the prediction of individual parameters in hierarchical models

Author

Listed:
  • Maryna Prus
  • Rainer Schwabe

Abstract

No abstract is available for this item.

Suggested Citation

  • Maryna Prus & Rainer Schwabe, 2016. "Optimal designs for the prediction of individual parameters in hierarchical models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 175-191, January.
    • Handle: RePEc:bla:jorssb:v:78:y:2016:i:1:p:175-191
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssb.12105
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maryna Prus, 2019. "Optimal designs for minimax-criteria in random coefficient regression models," Statistical Papers, Springer, vol. 60(2), pages 465-478, April.
    2. Lei He & Rong-Xian Yue, 2021. "D-optimal designs for hierarchical linear models with intraclass covariance structure," Statistical Papers, Springer, vol. 62(3), pages 1349-1361, June.
    3. Xin Liu & Rong-Xian Yue & Weng Kee Wong, 2019. "D-optimal designs for multi-response linear mixed models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(1), pages 87-98, January.
    4. Maryna Prus & Hans-Peter Piepho, 2021. "Optimizing the Allocation of Trials to Sub-regions in Multi-environment Crop Variety Testing," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(2), pages 267-288, June.
    5. Renata Eirini Tsirpitzi & Frank Miller & Carl-Fredrik Burman, 2023. "Robust optimal designs using a model misspecification term," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(7), pages 781-804, October.
    6. Prus, Maryna, 2019. "Various optimality criteria for the prediction of individual response curves," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 36-41.
    7. Liu, Xin & Yue, Rong-Xian & Chatterjee, Kashinath, 2020. "Geometric characterization of D-optimal designs for random coefficient regression models," Statistics & Probability Letters, Elsevier, vol. 159(C).
    8. Harman, Radoslav & Prus, Maryna, 2018. "Computing optimal experimental designs with respect to a compound Bayes risk criterion," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 135-141.
    9. Maryna Prus, 2023. "Optimal designs for prediction in random coefficient regression with one observation per individual," Statistical Papers, Springer, vol. 64(4), pages 1057-1068, August.
    10. Liu, Xin & Ye, Min & Yue, Rong-Xian, 2021. "Optimal designs for comparing population curves in hierarchical models," Statistics & Probability Letters, Elsevier, vol. 178(C).
    11. He, Lei & He, Daojiang, 2020. "R-optimal designs for individual prediction in random coefficient regression models," Statistics & Probability Letters, Elsevier, vol. 159(C).
    12. Xiao-Dong Zhou & Yun-Juan Wang & Rong-Xian Yue, 2018. "Robust population designs for longitudinal linear regression model with a random intercept," Computational Statistics, Springer, vol. 33(2), pages 903-931, June.
    13. Prus, Maryna, 2023. "Optimal designs for prediction of random effects in two-groups models with multivariate response," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
    14. Maryna Prus, 2020. "Optimal designs in multiple group random coefficient regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 233-254, March.
    15. Xin Liu & Rong‐Xian Yue & Weng Kee Wong, 2022. "Equivalence theorems for c and DA‐optimality for linear mixed effects models with applications to multitreatment group assignments in health care," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1842-1859, December.

    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:78:y:2016:i:1:p:175-191. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.