Orthogonal Regression and Equivariance [microform] / Eric Blankmeyer
- Bib ID:
- 5563576
- Format:
- Book and Microform
- Author:
- Blankmeyer, Eric
- Online Version:
- https://eric.ed.gov/?id=ED363648
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- Description:
-
- [Washington, D.C.] : Distributed by ERIC Clearinghouse, 1993
- 12 p.
- Summary:
-
Ordinary least-squares regression treats the variables asymmetrically, designating a dependent variable and one or more independent variables. When it is not obvious how to make this distinction, a researcher may prefer to use orthogonal regression, which treats the variables symmetrically. However, the usual procedure for orthogonal regression is not equivariant. A simple modification is proposed to overcome this serious defect. Illustrative computations involving 15 observations on 5 variables are provided, and a robust version of the method is discussed. The modified orthogonal regression allows a researcher to explore a symmetric, equivariant, and robust linear relationship among a set of variables. (Contains 6 references.) (Author/SLD)
- Notes:
- May also be available online. Address as at 14/8/18: https://eric.ed.gov/
- Reproduction:
- Microfiche. [Washington D.C.]: ERIC Clearinghouse microfiches : positive.
- Subject:
- Available From:
- ERIC
- Copyright:
-
In Copyright
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Copyright status was determined using the following information:
- Material type:
- Literary Dramatic Musical
- Published status:
- Published
- Publication date:
- 1993
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