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Regression Lines and the Linear Functional Relationship

D. V. Lindley
Supplement to the Journal of the Royal Statistical Society
Vol. 9, No. 2 (1947), pp. 218-244
Published by: Wiley for the Royal Statistical Society
DOI: 10.2307/2984115
Stable URL: http://www.jstor.org/stable/2984115
Page Count: 27
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Regression Lines and the Linear Functional Relationship
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Abstract

The first half of this paper solves the following problem: if there is a linear multiple regression between n variates, under what conditions will the regression continue to be linear when the variates are influenced by error? The new regression coefficients are obtained in terms of the original coefficients. This leads in the second half to a discussion of the use of regression lines and functional relationships in statistical methodology. In the case of normal distributions the problem of estimation is discussed at some length. Since the classical work has used least squares methods a section relating to this work is included and some criticisms offered.

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