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On the Use of Incomplete Prior Information in Regression Analysis

H. Theil
Journal of the American Statistical Association
Vol. 58, No. 302 (Jun., 1963), pp. 401-414
DOI: 10.2307/2283275
Stable URL: http://www.jstor.org/stable/2283275
Page Count: 14
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On the Use of Incomplete Prior Information in Regression Analysis
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Abstract

This article deals with the use of prior beliefs in the estimation of regression coefficients; in particular, it considers the problems that arise when the residual variance of the regression equation is unknown and it offers a large-sample solution. Additional contributions deal with testing the hypothesis that prior and sample information are compatible with each other; and with a scalar measure for the shares of these two kinds of information in the posterior precision.

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