A relationship between generalized and integrated mean square errors |
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Authors: | J L Hess R F Gunst |
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Institution: | 1. Kansas State University , Manhattan, Kansas, U.S.A;2. Southern Methodist University , Dallas, Texas, U.S.A |
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Abstract: | Generalised Mean squared error is a flexible measure of the adequancy of ? repression estimator. It allows specific characteristics of the regression model and its intended use to be In-corportated in the measure itself. Similarly, integrated mean squared error enables a researcher to stipulate particular regions of interest and wi ighting functions in the assessment of a prediction equation. The appeal of both measures is their ability to allow design or model characteristics to directly influence the evaluation of fitted regression models. In this note an e-quivalence of the two measures is established for correctly specified models. |
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Keywords: | regression models biased estimation generalized mean squared error integrated mean squared error |
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