If you need an accessible version of this item please contact JSTOR User Support

Practical Use of Higher Order Asymptotics for Multiparameter Exponential Families

Donald A. Pierce and Dawn Peters
Journal of the Royal Statistical Society. Series B (Methodological)
Vol. 54, No. 3 (1992), pp. 701-737
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/2345853
Page Count: 37
  • Download PDF
  • Cite this Item

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 need an accessible version of this item please contact JSTOR User Support
Practical Use of Higher Order Asymptotics for Multiparameter Exponential Families
Preview not available

Abstract

Recently developed asymptotics based on saddlepoint methods provide important practical methods for multiparameter exponential families, especially in generalized linear models. The aim here is to clarify and explore these. Attention is restricted to tests and confidence intervals regarding a single parametric function which can be represented as a natural parameter of a full rank exponential family. Excellent approximations to exact conditional inferences are often available, in terms of simple adjustments to the signed square root of the likelihood ratio statistic. The focus is on distinguishing between two aspects of the adjustments: one reducing effects of nuisance parameter estimation and the other adjusting for little information regarding the parameter of interest. Numerical results are given for some Poisson and multinomial models.

Page Thumbnails

  • Thumbnail: Page 
[701]
    [701]
  • Thumbnail: Page 
702
    702
  • Thumbnail: Page 
703
    703
  • Thumbnail: Page 
704
    704
  • Thumbnail: Page 
705
    705
  • Thumbnail: Page 
706
    706
  • Thumbnail: Page 
707
    707
  • Thumbnail: Page 
708
    708
  • Thumbnail: Page 
709
    709
  • Thumbnail: Page 
710
    710
  • Thumbnail: Page 
711
    711
  • Thumbnail: Page 
712
    712
  • Thumbnail: Page 
713
    713
  • Thumbnail: Page 
714
    714
  • Thumbnail: Page 
715
    715
  • Thumbnail: Page 
716
    716
  • Thumbnail: Page 
717
    717
  • Thumbnail: Page 
718
    718
  • Thumbnail: Page 
719
    719
  • Thumbnail: Page 
720
    720
  • Thumbnail: Page 
721
    721
  • Thumbnail: Page 
722
    722
  • Thumbnail: Page 
723
    723
  • Thumbnail: Page 
724
    724
  • Thumbnail: Page 
725
    725
  • Thumbnail: Page 
726
    726
  • Thumbnail: Page 
727
    727
  • Thumbnail: Page 
728
    728
  • Thumbnail: Page 
729
    729
  • Thumbnail: Page 
730
    730
  • Thumbnail: Page 
731
    731
  • Thumbnail: Page 
732
    732
  • Thumbnail: Page 
733
    733
  • Thumbnail: Page 
734
    734
  • Thumbnail: Page 
735
    735
  • Thumbnail: Page 
736
    736
  • Thumbnail: Page 
737
    737