IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-94-009-7840-9_26.html
   My bibliography  Save this book chapter

Polynomials of Parameters in the Regression Model — Estimation and Design

In: Probability and Statistical Inference

Author

Listed:
  • A. Pázman

    (Slovak Academy of Sciences, Mathematical Institute, Electro-Physical Research Centre)

  • J. Volaufová

    (Slovak Academy of Sciences, Institute of Measurement and Measuring Technique Electro-Physical Research Centre)

Abstract

The regression model $$y({x_i}) = \sum {_{j = 1}^m} {f_j}({x_i}){\theta _j} + \varepsilon ({x_i})$$ is considered, with $$ (\varepsilon ({x_1}), \ldots ,\varepsilon ({x_N})) \sim N(0,K),K $$ K known. The aim of the paper is to consider unbiased estimates of polynomials in the variables θl,…,θm. An explicit expression for the minimum variance unbiased estimate is given and bounds for the variance of this estimate are given. A criterion of optimality of the design is considered and an algorithm for computing the optimum design in the case of uncorrelated observations is presented.

Suggested Citation

  • A. Pázman & J. Volaufová, 1982. "Polynomials of Parameters in the Regression Model — Estimation and Design," Springer Books, in: Wilfried Grossmann & Georg Ch. Pflug & Wolfgang Wertz (ed.), Probability and Statistical Inference, pages 275-285, Springer.
    • Handle: RePEc:spr:sprchp:978-94-009-7840-9_26
    DOI: 10.1007/978-94-009-7840-9_26
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-94-009-7840-9_26. 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: 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.