IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v60y2019i2d10.1007_s00362-018-01078-4.html
   My bibliography  Save this article

Locally D-optimal designs for a wider class of non-linear models on the k-dimensional ball

Author

Listed:
  • Martin Radloff

    (Otto-von-Guericke-University)

  • Rainer Schwabe

    (Otto-von-Guericke-University)

Abstract

In this paper we extend the results of Radloff and Schwabe ( arXiv:1806.00275 , 2018), which could be applied for example to Poisson regression, negative binomial regression and proportional hazard models with censoring, to a wider class of non-linear multiple regression models. This includes the binary response models with logit and probit link besides others. For this class of models we derive (locally) D-optimal designs when the design region is a k-dimensional ball. For the corresponding construction we make use of the concept of invariance and equivariance in the context of optimal designs as in our previous paper. In contrast to the former results the designs will not necessarily be exact designs in all cases. Instead approximate designs can appear. These results can be generalized to arbitrary ellipsoidal design regions.

Suggested Citation

  • Martin Radloff & Rainer Schwabe, 2019. "Locally D-optimal designs for a wider class of non-linear models on the k-dimensional ball," Statistical Papers, Springer, vol. 60(2), pages 515-527, April.
    • Handle: RePEc:spr:stpapr:v:60:y:2019:i:2:d:10.1007_s00362-018-01078-4
    DOI: 10.1007/s00362-018-01078-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-018-01078-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00362-018-01078-4?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. Biedermann, Stefanie & Dette, Holger & Zhu, Wei, 2006. "Optimal Designs for DoseResponse Models With Restricted Design Spaces," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 747-759, June.
    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. Niaparast, Mehrdad, 2009. "On optimal design for a Poisson regression model with random intercept," Statistics & Probability Letters, Elsevier, vol. 79(6), pages 741-747, March.
    2. Dette, Holger & Holland-Letz, Tim, 2008. "A geometric characterization of c-optimal designs for heteroscedastic regression," Technical Reports 2008,26, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Karvanen, Juha, 2009. "Approximate cost-efficient sequential designs for binary response models with application to switching measurements," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1167-1176, February.
    4. Nancy Flournoy & José Moler & Fernando Plo, 2020. "Performance Measures in Dose‐Finding Experiments," International Statistical Review, International Statistical Institute, vol. 88(3), pages 728-751, December.
    5. repec:jss:jstsof:35:i06 is not listed on IDEAS
    6. Dorta-Guerra, Roberto & González-Dávila, Enrique & Ginebra, Josep, 2008. "Two-level experiments for binary response data," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 196-208, September.

    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:60:y:2019:i:2:d:10.1007_s00362-018-01078-4. 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.