The Joint Treatment of Exact and Stochastic Restrictions |
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Authors: | J S Shonkwiler |
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Institution: | Institute of Food and Agricultural Sciences, University of Florida |
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Abstract: | In regression analysis both exact and stochastic extraneous information may be represented via restrictions on the parameters of a linear model which then may be estimated by applying constrained generalized least squares. It is shown that this estimator can be recast as a computationally simpler estimator that is a combination of the ordinary least squares estimator and the discrepancy between the OLS estimator and both types of restrictions. The variance of the restricted parameters is explicitly shown to depend on the variance of the extraneous information. |
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