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A relationship between generalized and integrated mean square errors
Authors:J L Hess  R F Gunst
Institution:1. Kansas State University , Manhattan, Kansas, U.S.A;2. Southern Methodist University , Dallas, Texas, U.S.A
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.
Keywords:regression models  biased estimation  generalized mean squared error  integrated mean squared error
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