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.

Bounded Influence Estimation in the Mixed Linear Model

Alice M. Richardson
Journal of the American Statistical Association
Vol. 92, No. 437 (Mar., 1997), pp. 154-161
DOI: 10.2307/2291459
Stable URL: http://www.jstor.org/stable/2291459
Page Count: 8
  • Download ($14.00)
  • Cite this Item
Bounded Influence Estimation in the Mixed Linear Model
Preview not available

Abstract

Bounded influence estimation (also known as generalized M or GM estimation) in the regression model is reviewed. The definitions of bounded influence estimation proposed by Mallows and Schweppe are then extended to the mixed linear model. This is achieved by applying appropriate weight functions to maximum likelihood and restricted maximum likelihood estimating equations. The asymptotic properties of the new estimators are obtained, and the estimators are applied to an artificial dataset. The article concludes with an extension of the example into a small simulation study designed to test some properties of the estimators in samples of moderate size.

Page Thumbnails

  • Thumbnail: Page 
154
    154
  • Thumbnail: Page 
155
    155
  • Thumbnail: Page 
156
    156
  • Thumbnail: Page 
157
    157
  • Thumbnail: Page 
158
    158
  • Thumbnail: Page 
159
    159
  • Thumbnail: Page 
160
    160
  • Thumbnail: Page 
161
    161