Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

Some Applications of Canonical Moments in Fourier Regression Models

Holger Dette
Lecture Notes-Monograph Series
Vol. 34, New Developments and Applications in Experimental Design (1998), pp. 175-185
Stable URL: http://www.jstor.org/stable/4356072
Page Count: 11
  • Read Online (Free)
  • Download ($19.00)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Some Applications of Canonical Moments in Fourier Regression Models
Preview not available

Abstract

This paper applies recent results on canonical moments for the determination of optimal designs for multivariate Fourier regression models. Optimal designs for discriminating between different Fourier regression models can be found explicitly. It is also demonstrated that these designs may be useful in orthogonal series estimation and for testing additivity in nonparametric regression. In contrast to many other optimality criteria for the trigonometric regression model, the discrimination designs are not necessarily uniformly distributed on equidistant points.

Page Thumbnails

  • Thumbnail: Page 
175
    175
  • Thumbnail: Page 
176
    176
  • Thumbnail: Page 
177
    177
  • Thumbnail: Page 
178
    178
  • Thumbnail: Page 
179
    179
  • Thumbnail: Page 
180
    180
  • Thumbnail: Page 
181
    181
  • Thumbnail: Page 
182
    182
  • Thumbnail: Page 
183
    183
  • Thumbnail: Page 
184
    184
  • Thumbnail: Page 
185
    185