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Statistical Properties of Estimates of Linear Models
Vol. 18, No. 3 (Aug., 1976), pp. 283-289
Published by: Taylor & Francis, Ltd. on behalf of American Statistical Association and American Society for Quality
Stable URL: http://www.jstor.org/stable/1268737
Page Count: 7
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The selection of the best subset of variables in a linear model is generally produced by obtaining the regression equation that satisfies an optimality criterion. Unfortunately the statistical properties of the selected regression equations are not described by a general theory and in fact very little is known of these properties. In this paper the different possible models are compared in terms of a risk function. The properties of the risk function are used to study the effect of rejecting non-significant variables.
Technometrics © 1976 American Statistical Association