SHRINKAGE REGRESSION PREDICTORS FOR PREDICTION AREA DIFFERENT FROM SAMPLE AREA

Abstract

In a linear regression model, some shrinkage type regression predictors are examined in a situation where a prediction area is different from a sample area. This is then evaluated from the perspective of an estimation error of shrinkage parameter to estimate from a sample. The goodness of the shrinkage regression predictor is appraised on the basis of the expectation of Prediction Mean Square Error (PMSE) with respect to the model condition parameter following a prior distribution. A modified shrinkage predictor is proposed.