Access

You are not currently logged in.

Access JSTOR through your library or other institution:

login

Log in through your institution.

Journal Article

The Hat Matrix in Regression and ANOVA

David C. Hoaglin and Roy E. Welsch
The American Statistician
Vol. 32, No. 1 (Feb., 1978), pp. 17-22
DOI: 10.2307/2683469
Stable URL: http://www.jstor.org/stable/2683469
Page Count: 6
Were these topics helpful?
See somethings inaccurate? Let us know!

Select the topics that are inaccurate.

Cancel
  • Download ($14.00)
  • Add to My Lists
  • Cite this Item
The Hat Matrix in Regression and ANOVA
Preview not available

Abstract

In least-squares fitting it is important to understand the influence which a data y value will have on each fitted y value. A projection matrix known as the hat matrix contains this information and, together with the Studentized residuals, provides a means of identifying exceptional data points. This approach also simplifies the calculations involved in removing a data point, and it requires only simple modifications in the preferred numerical least-squares algorithms.

Page Thumbnails

  • Thumbnail: Page 
17
    17
  • Thumbnail: Page 
18
    18
  • Thumbnail: Page 
19
    19
  • Thumbnail: Page 
20
    20
  • Thumbnail: Page 
21
    21
  • Thumbnail: Page 
22
    22